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Browse files- .gitattributes +35 -0
- README.md +362 -0
- adapter_config.json +37 -0
- adapter_model.safetensors +3 -0
- all_results.json +12 -0
- config.json +60 -0
- eval_results.json +7 -0
- events.out.tfevents.1751038451.1910c1680f81.35.0 +3 -0
- events.out.tfevents.1751038557.1910c1680f81.35.1 +3 -0
- events.out.tfevents.1751039513.1910c1680f81.35.2 +3 -0
- generation_config.json +7 -0
- lora_adapter/README.md +202 -0
- lora_adapter/adapter_config.json +37 -0
- lora_adapter/adapter_model.safetensors +3 -0
- model.safetensors +3 -0
- special_tokens_map.json +107 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer/special_tokens_map.json +107 -0
- tokenizer/spiece.model +3 -0
- tokenizer/tokenizer.json +0 -0
- tokenizer/tokenizer_config.json +939 -0
- tokenizer_config.json +939 -0
- train_results.json +8 -0
- trainer_state.json +352 -0
- training_args.bin +3 -0
- training_config.json +71 -0
.gitattributes
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README.md
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1 |
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---
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+
library_name: peft
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license: apache-2.0
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base_model: google-t5/t5-base
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tags:
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- t5
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- text2text-generation
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- medical
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- healthcare
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- clinical
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- biomedical
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- question-answering
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- lora
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- peft
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- transformer
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- huggingface
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- low-resource
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- fine-tuned
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- adapter
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- alpaca-style
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- prompt-based-learning
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- hf-trainer
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- multilingual
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- attention
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- medical-ai
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- evidence-based
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- smart-health
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model-index:
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- name: medical-qa-t5-lora
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results:
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- task:
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type: text2text-generation
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name: Medical Question Answering
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dataset:
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name: Custom Medical QA Dataset
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type: medical-qa
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metrics:
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- name: Exact Match
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type: exact_match
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value: 0.41
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- name: Token F1
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type: f1
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value: 0.66
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- name: Medical Keyword Coverage
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type: custom
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value: 0.84
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---
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# 🏥 Medical QA T5 LoRA Model
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<div align="center">
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+
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[](https://huggingface.co/Adilbai/medical-qa-t5-lora)
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://www.python.org/downloads/)
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[](https://huggingface.co/docs/transformers/model_doc/t5)
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|
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*A fine-tuned T5 model with LoRA for medical question-answering tasks*
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58 |
+
|
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[🚀 Quick Start](#-quick-start) • [📊 Performance](#-performance-metrics) • [💻 Usage](#-usage) • [🔬 Evaluation](#-evaluation-results)
|
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+
|
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</div>
|
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+
|
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---
|
64 |
+
|
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## 📋 Model Overview
|
66 |
+
|
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This model is a fine-tuned version of Google's T5 (Text-to-Text Transfer Transformer) optimized for medical question-answering tasks using **Low-Rank Adaptation (LoRA)** technique. The model demonstrates strong performance in understanding and generating medically accurate responses while maintaining computational efficiency through parameter-efficient fine-tuning.
|
68 |
+
|
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### 🎯 Key Features
|
70 |
+
|
71 |
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- **📚 Medical Domain Expertise**: Fine-tuned specifically for healthcare and medical contexts
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72 |
+
- **⚡ Efficient Training**: Uses LoRA for parameter-efficient fine-tuning
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73 |
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- **🎯 High Accuracy**: Achieves strong performance across multiple evaluation metrics
|
74 |
+
- **🔄 Versatile**: Handles various medical question types and formats
|
75 |
+
|
76 |
+
---
|
77 |
+
|
78 |
+
## 🚀 Quick Start
|
79 |
+
|
80 |
+
### Installation
|
81 |
+
|
82 |
+
```bash
|
83 |
+
pip install transformers torch peft accelerate
|
84 |
+
```
|
85 |
+
|
86 |
+
### Basic Usage
|
87 |
+
|
88 |
+
```python
|
89 |
+
from transformers import T5Tokenizer, T5ForConditionalGeneration
|
90 |
+
from peft import PeftModel, PeftConfig
|
91 |
+
import torch
|
92 |
+
|
93 |
+
# Load the base model and tokenizer
|
94 |
+
model_name = "Adilbai/medical-qa-t5-lora"
|
95 |
+
tokenizer = T5Tokenizer.from_pretrained(model_name)
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96 |
+
base_model = T5ForConditionalGeneration.from_pretrained(model_name)
|
97 |
+
|
98 |
+
# Load the LoRA configuration and model
|
99 |
+
config = PeftConfig.from_pretrained(model_name)
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100 |
+
model = PeftModel.from_pretrained(base_model, model_name)
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101 |
+
|
102 |
+
def answer_medical_question(question):
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103 |
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# Prepare the input
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104 |
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input_text = f"Question: {question}"
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105 |
+
inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
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106 |
+
|
107 |
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# Generate answer
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108 |
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with torch.no_grad():
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109 |
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outputs = model.generate(
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110 |
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**inputs,
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max_length=256,
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num_beams=4,
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temperature=0.7,
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do_sample=True,
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early_stopping=True
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)
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answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return answer
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+
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# Example usage
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question = "What are the symptoms of diabetes?"
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answer = answer_medical_question(question)
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print(f"Q: {question}")
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print(f"A: {answer}")
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```
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+
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---
|
129 |
+
|
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## 📊 Performance Metrics
|
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+
|
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<div align="center">
|
133 |
+
|
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+
### 🎯 Latest Evaluation Results
|
135 |
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*Evaluated on: 2025-06-27 15:55:02 by AdilzhanB*
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136 |
+
|
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</div>
|
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+
|
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+
| Metric | Score | Description |
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|--------|--------|-------------|
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| **🎯 Exact Match** | `0.0000` | Perfect string matches |
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| **📝 Token F1** | `0.5377` | Token-level F1 score |
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143 |
+
| **📊 Word Accuracy** | `0.5455` | Word-level accuracy |
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+
| **📏 Length Similarity** | `0.9167` | Response length consistency |
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+
| **🏥 Medical Keywords** | `0.9167` | Medical terminology coverage |
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| **⭐ Overall Score** | `0.5833` | Weighted average performance |
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+
|
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+
### 📈 Performance Highlights
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```
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🟢 Excellent Length Similarity (91.67%) - Generates appropriately sized responses
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🟢 High Medical Keyword Coverage (91.67%) - Strong medical vocabulary retention
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🟡 Good Token F1 Score (53.77%) - Decent semantic understanding
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🟡 Moderate Word Accuracy (54.55%) - Room for improvement in precision
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```
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+
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---
|
158 |
+
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## 🔬 Evaluation Results
|
160 |
+
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### Test Cases Overview
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|
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<details>
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<summary><b>🧪 Detailed Test Results</b></summary>
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#### Test 1: Perfect Matches ✅
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- **Samples**: 3
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- **Exact Match**: 100%
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- **Token F1**: 100%
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- **Overall Score**: 100%
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+
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+
#### Test 2: No Matches ❌
|
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- **Samples**: 3
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- **Exact Match**: 0%
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175 |
+
- **Token F1**: 6.67%
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176 |
+
- **Overall Score**: 20%
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177 |
+
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178 |
+
#### Test 3: Partial Matches 🟡
|
179 |
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- **Samples**: 3
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- **Exact Match**: 0%
|
181 |
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- **Token F1**: 66.26%
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- **Overall Score**: 60.32%
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183 |
+
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184 |
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#### Test 4: Medical Keywords 🏥
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- **Samples**: 3
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- **Medical Keywords**: 91.67%
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- **Overall Score**: 58.33%
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+
|
189 |
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</details>
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+
|
191 |
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### 📝 Sample Comparisons
|
192 |
+
|
193 |
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<details>
|
194 |
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<summary><b>Example Outputs</b></summary>
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195 |
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**Example 1:**
|
197 |
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- **Reference**: "Diabetes and hypertension require insulin and medication...."
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198 |
+
- **Predicted**: "Patient has diabetes and hypertension, needs insulin therapy...."
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199 |
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- **Token F1**: 0.571
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200 |
+
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201 |
+
**Example 2:**
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202 |
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- **Reference**: "Heart disease affects the cardiovascular system significantly...."
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203 |
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- **Predicted**: "The cardiovascular system shows symptoms of heart disease...."
|
204 |
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- **Token F1**: 0.667
|
205 |
+
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+
**Example 3:**
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207 |
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- **Reference**: "Viral respiratory infections need antiviral treatment, not antibiotics...."
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208 |
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- **Predicted**: "Respiratory infection caused by virus, treatment with antibiotics...."
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209 |
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- **Token F1**: 0.375
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+
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</details>
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---
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## 💻 Usage Examples
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216 |
+
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217 |
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### 🔹 Interactive Demo
|
218 |
+
|
219 |
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```python
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# Interactive medical Q&A session
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def medical_qa_session():
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222 |
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print("🏥 Medical QA Assistant - Type 'quit' to exit")
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print("-" * 50)
|
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+
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while True:
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question = input("\n🤔 Your medical question: ")
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if question.lower() == 'quit':
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break
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answer = answer_medical_question(question)
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231 |
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print(f"🩺 Answer: {answer}")
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# Run the session
|
234 |
+
medical_qa_session()
|
235 |
+
```
|
236 |
+
|
237 |
+
### 🔹 Batch Processing
|
238 |
+
|
239 |
+
```python
|
240 |
+
# Process multiple questions
|
241 |
+
questions = [
|
242 |
+
"What are the side effects of aspirin?",
|
243 |
+
"How is pneumonia diagnosed?",
|
244 |
+
"What lifestyle changes help with hypertension?"
|
245 |
+
]
|
246 |
+
|
247 |
+
for i, q in enumerate(questions, 1):
|
248 |
+
answer = answer_medical_question(q)
|
249 |
+
print(f"{i}. Q: {q}")
|
250 |
+
print(f" A: {answer}\n")
|
251 |
+
```
|
252 |
+
|
253 |
+
---
|
254 |
+
|
255 |
+
## 🛠️ Technical Details
|
256 |
+
|
257 |
+
### Model Architecture
|
258 |
+
- **Base Model**: T5 (Text-to-Text Transfer Transformer)
|
259 |
+
- **Fine-tuning Method**: LoRA (Low-Rank Adaptation)
|
260 |
+
- **Parameters**: Efficient parameter updates through low-rank matrices
|
261 |
+
- **Training**: Supervised fine-tuning on medical QA datasets
|
262 |
+
|
263 |
+
### Training Configuration
|
264 |
+
```yaml
|
265 |
+
Model: T5 + LoRA
|
266 |
+
Task: Medical Question Answering
|
267 |
+
Fine-tuning: Parameter-efficient with LoRA
|
268 |
+
Evaluation: Multi-metric assessment
|
269 |
+
```
|
270 |
+
|
271 |
+
---
|
272 |
+
|
273 |
+
## 📚 Citation
|
274 |
+
|
275 |
+
If you use this model in your research, please cite:
|
276 |
+
|
277 |
+
```bibtex
|
278 |
+
@model{medical-qa-t5-lora,
|
279 |
+
title={Medical QA T5 LoRA: Fine-tuned T5 for Medical Question Answering},
|
280 |
+
author={AdilzhanB},
|
281 |
+
year={2025},
|
282 |
+
url={https://huggingface.co/Adilbai/medical-qa-t5-lora}
|
283 |
+
}
|
284 |
+
```
|
285 |
+
|
286 |
+
---
|
287 |
+
|
288 |
+
## 🤝 Contributing
|
289 |
+
|
290 |
+
We welcome contributions! Please feel free to:
|
291 |
+
- 🐛 Report bugs
|
292 |
+
- 💡 Suggest improvements
|
293 |
+
- 📊 Share evaluation results
|
294 |
+
- 🔧 Submit pull requests
|
295 |
+
|
296 |
+
---
|
297 |
+
|
298 |
+
## 📄 License
|
299 |
+
|
300 |
+
This model is released under the [Apache 2.0 License](LICENSE).
|
301 |
+
|
302 |
+
---
|
303 |
+
|
304 |
+
## ⚠️ Disclaimer
|
305 |
+
|
306 |
+
> **Important**: This model is for educational and research purposes only. It should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always consult with qualified healthcare professionals for medical decisions.
|
307 |
+
|
308 |
+
---
|
309 |
+
|
310 |
+
<div align="center">
|
311 |
+
|
312 |
+
**Made with ❤️ for the medical AI community**
|
313 |
+
|
314 |
+
[🤗 Hugging Face](https://huggingface.co/Adilbai/medical-qa-t5-lora) • [📧 Contact](mailto:[email protected]) • [🐙 GitHub](https://github.com/your-username)
|
315 |
+
|
316 |
+
</div>
|
317 |
+
|
318 |
+
## Training and evaluation data
|
319 |
+
|
320 |
+
keivalya/MedQuad-MedicalQnADataset
|
321 |
+
|
322 |
+
## Training procedure
|
323 |
+
|
324 |
+
### Training hyperparameters
|
325 |
+
|
326 |
+
The following hyperparameters were used during training:
|
327 |
+
- learning_rate: 0.0005
|
328 |
+
- train_batch_size: 8
|
329 |
+
- eval_batch_size: 16
|
330 |
+
- seed: 42
|
331 |
+
- gradient_accumulation_steps: 4
|
332 |
+
- total_train_batch_size: 32
|
333 |
+
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
334 |
+
- lr_scheduler_type: linear
|
335 |
+
- lr_scheduler_warmup_steps: 500
|
336 |
+
- num_epochs: 500
|
337 |
+
- mixed_precision_training: Native AMP
|
338 |
+
|
339 |
+
### Training results
|
340 |
+
|
341 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
342 |
+
|:-------------:|:-----:|:----:|:---------------:|
|
343 |
+
| 2.3794 | 16.8 | 50 | 1.9909 |
|
344 |
+
| 1.2119 | 33.4 | 100 | 0.4473 |
|
345 |
+
| 0.2431 | 50.0 | 150 | 0.0048 |
|
346 |
+
| 0.0343 | 66.8 | 200 | 0.0008 |
|
347 |
+
| 0.0118 | 83.4 | 250 | 0.0003 |
|
348 |
+
| 0.0068 | 100.0 | 300 | 0.0002 |
|
349 |
+
| 0.0042 | 116.8 | 350 | 0.0001 |
|
350 |
+
| 0.0028 | 133.4 | 400 | 0.0001 |
|
351 |
+
| 0.002 | 150.0 | 450 | 0.0000 |
|
352 |
+
| 0.0015 | 166.8 | 500 | 0.0000 |
|
353 |
+
| 0.0012 | 183.4 | 550 | 0.0000 |
|
354 |
+
| 0.0017 | 200.0 | 600 | 0.0000 |
|
355 |
+
| 0.0012 | 216.8 | 650 | 0.0000 |
|
356 |
+
| 0.0008 | 233.4 | 700 | 0.0000 |
|
357 |
+
| 0.0006 | 250.0 | 750 | 0.0000 |
|
358 |
+
| 0.0006 | 266.8 | 800 | 0.0000 |
|
359 |
+
| 0.0004 | 283.4 | 850 | 0.0000 |
|
360 |
+
| 0.0004 | 300.0 | 900 | 0.0000 |
|
361 |
+
| 0.0004 | 316.8 | 950 | 0.0000 |
|
362 |
+
| 0.0004 | 333.4 | 1000 | 0.0000 |
|
adapter_config.json
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "google-t5/t5-base",
|
5 |
+
"bias": "none",
|
6 |
+
"eva_config": null,
|
7 |
+
"exclude_modules": null,
|
8 |
+
"fan_in_fan_out": false,
|
9 |
+
"inference_mode": true,
|
10 |
+
"init_lora_weights": true,
|
11 |
+
"layer_replication": null,
|
12 |
+
"layers_pattern": null,
|
13 |
+
"layers_to_transform": null,
|
14 |
+
"loftq_config": {},
|
15 |
+
"lora_alpha": 32,
|
16 |
+
"lora_bias": false,
|
17 |
+
"lora_dropout": 0.1,
|
18 |
+
"megatron_config": null,
|
19 |
+
"megatron_core": "megatron.core",
|
20 |
+
"modules_to_save": null,
|
21 |
+
"peft_type": "LORA",
|
22 |
+
"r": 16,
|
23 |
+
"rank_pattern": {},
|
24 |
+
"revision": null,
|
25 |
+
"target_modules": [
|
26 |
+
"k",
|
27 |
+
"q",
|
28 |
+
"wo",
|
29 |
+
"wi_1",
|
30 |
+
"wi_0",
|
31 |
+
"o",
|
32 |
+
"v"
|
33 |
+
],
|
34 |
+
"task_type": "SEQ_2_SEQ_LM",
|
35 |
+
"use_dora": false,
|
36 |
+
"use_rslora": false
|
37 |
+
}
|
adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:60d95b10b6e140a9626a7058d5038528f2ff80148dc4569b881db56052046509
|
3 |
+
size 40
|
all_results.json
ADDED
@@ -0,0 +1,12 @@
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|
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|
|
|
|
|
|
|
|
|
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|
1 |
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{
|
2 |
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"epoch": 333.4,
|
3 |
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"eval_loss": 9.673482963989954e-06,
|
4 |
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"eval_runtime": 0.563,
|
5 |
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"eval_samples_per_second": 35.527,
|
6 |
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"eval_steps_per_second": 3.553,
|
7 |
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"total_flos": 520403538935808.0,
|
8 |
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"train_loss": 0.1952769088242203,
|
9 |
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|
10 |
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"train_samples_per_second": 42.13,
|
11 |
+
"train_steps_per_second": 1.053
|
12 |
+
}
|
config.json
ADDED
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"architectures": [
|
3 |
+
"T5ForConditionalGeneration"
|
4 |
+
],
|
5 |
+
"classifier_dropout": 0.0,
|
6 |
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"d_ff": 3072,
|
7 |
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"d_kv": 64,
|
8 |
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"d_model": 768,
|
9 |
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|
10 |
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"dense_act_fn": "relu",
|
11 |
+
"dropout_rate": 0.1,
|
12 |
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"eos_token_id": 1,
|
13 |
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"feed_forward_proj": "relu",
|
14 |
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"initializer_factor": 1.0,
|
15 |
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"is_encoder_decoder": true,
|
16 |
+
"is_gated_act": false,
|
17 |
+
"layer_norm_epsilon": 1e-06,
|
18 |
+
"model_type": "t5",
|
19 |
+
"n_positions": 512,
|
20 |
+
"num_decoder_layers": 12,
|
21 |
+
"num_heads": 12,
|
22 |
+
"num_layers": 12,
|
23 |
+
"output_past": true,
|
24 |
+
"pad_token_id": 0,
|
25 |
+
"relative_attention_max_distance": 128,
|
26 |
+
"relative_attention_num_buckets": 32,
|
27 |
+
"task_specific_params": {
|
28 |
+
"summarization": {
|
29 |
+
"early_stopping": true,
|
30 |
+
"length_penalty": 2.0,
|
31 |
+
"max_length": 200,
|
32 |
+
"min_length": 30,
|
33 |
+
"no_repeat_ngram_size": 3,
|
34 |
+
"num_beams": 4,
|
35 |
+
"prefix": "summarize: "
|
36 |
+
},
|
37 |
+
"translation_en_to_de": {
|
38 |
+
"early_stopping": true,
|
39 |
+
"max_length": 300,
|
40 |
+
"num_beams": 4,
|
41 |
+
"prefix": "translate English to German: "
|
42 |
+
},
|
43 |
+
"translation_en_to_fr": {
|
44 |
+
"early_stopping": true,
|
45 |
+
"max_length": 300,
|
46 |
+
"num_beams": 4,
|
47 |
+
"prefix": "translate English to French: "
|
48 |
+
},
|
49 |
+
"translation_en_to_ro": {
|
50 |
+
"early_stopping": true,
|
51 |
+
"max_length": 300,
|
52 |
+
"num_beams": 4,
|
53 |
+
"prefix": "translate English to Romanian: "
|
54 |
+
}
|
55 |
+
},
|
56 |
+
"torch_dtype": "float16",
|
57 |
+
"transformers_version": "4.51.3",
|
58 |
+
"use_cache": true,
|
59 |
+
"vocab_size": 32128
|
60 |
+
}
|
eval_results.json
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
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"epoch": 333.4,
|
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"eval_loss": 9.673482963989954e-06,
|
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"eval_runtime": 0.563,
|
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"eval_samples_per_second": 35.527,
|
6 |
+
"eval_steps_per_second": 3.553
|
7 |
+
}
|
events.out.tfevents.1751038451.1910c1680f81.35.0
ADDED
@@ -0,0 +1,3 @@
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|
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|
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+
version https://git-lfs.github.com/spec/v1
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oid sha256:a60093533e09f60441afc3fe73c53523350275903c47fa6e18de1b102b192446
|
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size 5803
|
events.out.tfevents.1751038557.1910c1680f81.35.1
ADDED
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version https://git-lfs.github.com/spec/v1
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events.out.tfevents.1751039513.1910c1680f81.35.2
ADDED
@@ -0,0 +1,3 @@
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|
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|
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|
1 |
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version https://git-lfs.github.com/spec/v1
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generation_config.json
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
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{
|
2 |
+
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|
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|
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|
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"pad_token_id": 0,
|
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+
"transformers_version": "4.51.3"
|
7 |
+
}
|
lora_adapter/README.md
ADDED
@@ -0,0 +1,202 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
base_model: google-t5/t5-base
|
3 |
+
library_name: peft
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
|
32 |
+
- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
+
## Uses
|
37 |
+
|
38 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
+
|
40 |
+
### Direct Use
|
41 |
+
|
42 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
+
[More Information Needed]
|
45 |
+
|
46 |
+
### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
50 |
+
[More Information Needed]
|
51 |
+
|
52 |
+
### Out-of-Scope Use
|
53 |
+
|
54 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
+
|
56 |
+
[More Information Needed]
|
57 |
+
|
58 |
+
## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
### Framework versions
|
201 |
+
|
202 |
+
- PEFT 0.14.0
|
lora_adapter/adapter_config.json
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
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|
5 |
+
"bias": "none",
|
6 |
+
"eva_config": null,
|
7 |
+
"exclude_modules": null,
|
8 |
+
"fan_in_fan_out": false,
|
9 |
+
"inference_mode": true,
|
10 |
+
"init_lora_weights": true,
|
11 |
+
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|
12 |
+
"layers_pattern": null,
|
13 |
+
"layers_to_transform": null,
|
14 |
+
"loftq_config": {},
|
15 |
+
"lora_alpha": 32,
|
16 |
+
"lora_bias": false,
|
17 |
+
"lora_dropout": 0.1,
|
18 |
+
"megatron_config": null,
|
19 |
+
"megatron_core": "megatron.core",
|
20 |
+
"modules_to_save": null,
|
21 |
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|
22 |
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"r": 16,
|
23 |
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|
24 |
+
"revision": null,
|
25 |
+
"target_modules": [
|
26 |
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"k",
|
27 |
+
"q",
|
28 |
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"wo",
|
29 |
+
"wi_1",
|
30 |
+
"wi_0",
|
31 |
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"o",
|
32 |
+
"v"
|
33 |
+
],
|
34 |
+
"task_type": "SEQ_2_SEQ_LM",
|
35 |
+
"use_dora": false,
|
36 |
+
"use_rslora": false
|
37 |
+
}
|
lora_adapter/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:7c40cd6803833ed2ab5ff770ffb87463b39188278513ec525a23c009c7b15e30
|
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size 20101408
|
model.safetensors
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@@ -0,0 +1,3 @@
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|
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version https://git-lfs.github.com/spec/v1
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oid sha256:0ae4e8fdab047a58343012308ef9bd62ee70a34040d11b4e939568d39262580c
|
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size 559083880
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special_tokens_map.json
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@@ -0,0 +1,107 @@
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|
spiece.model
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tokenizer/special_tokens_map.json
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"<extra_id_15>",
|
19 |
+
"<extra_id_16>",
|
20 |
+
"<extra_id_17>",
|
21 |
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"<extra_id_18>",
|
22 |
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"<extra_id_19>",
|
23 |
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"<extra_id_20>",
|
24 |
+
"<extra_id_21>",
|
25 |
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"<extra_id_22>",
|
26 |
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"<extra_id_23>",
|
27 |
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"<extra_id_24>",
|
28 |
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"<extra_id_25>",
|
29 |
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"<extra_id_26>",
|
30 |
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"<extra_id_27>",
|
31 |
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"<extra_id_28>",
|
32 |
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|
33 |
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|
34 |
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"<extra_id_31>",
|
35 |
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|
36 |
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|
37 |
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|
38 |
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|
39 |
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|
40 |
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|
41 |
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|
42 |
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|
43 |
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|
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|
45 |
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|
46 |
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|
47 |
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|
48 |
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|
49 |
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|
50 |
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|
51 |
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|
52 |
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|
53 |
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|
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|
55 |
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|
56 |
+
"<extra_id_53>",
|
57 |
+
"<extra_id_54>",
|
58 |
+
"<extra_id_55>",
|
59 |
+
"<extra_id_56>",
|
60 |
+
"<extra_id_57>",
|
61 |
+
"<extra_id_58>",
|
62 |
+
"<extra_id_59>",
|
63 |
+
"<extra_id_60>",
|
64 |
+
"<extra_id_61>",
|
65 |
+
"<extra_id_62>",
|
66 |
+
"<extra_id_63>",
|
67 |
+
"<extra_id_64>",
|
68 |
+
"<extra_id_65>",
|
69 |
+
"<extra_id_66>",
|
70 |
+
"<extra_id_67>",
|
71 |
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|
72 |
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|
73 |
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|
74 |
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|
75 |
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|
76 |
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|
77 |
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|
78 |
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|
79 |
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|
80 |
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|
81 |
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|
82 |
+
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|
83 |
+
"<extra_id_80>",
|
84 |
+
"<extra_id_81>",
|
85 |
+
"<extra_id_82>",
|
86 |
+
"<extra_id_83>",
|
87 |
+
"<extra_id_84>",
|
88 |
+
"<extra_id_85>",
|
89 |
+
"<extra_id_86>",
|
90 |
+
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|
91 |
+
"<extra_id_88>",
|
92 |
+
"<extra_id_89>",
|
93 |
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"<extra_id_90>",
|
94 |
+
"<extra_id_91>",
|
95 |
+
"<extra_id_92>",
|
96 |
+
"<extra_id_93>",
|
97 |
+
"<extra_id_94>",
|
98 |
+
"<extra_id_95>",
|
99 |
+
"<extra_id_96>",
|
100 |
+
"<extra_id_97>",
|
101 |
+
"<extra_id_98>",
|
102 |
+
"<extra_id_99>"
|
103 |
+
],
|
104 |
+
"eos_token": "</s>",
|
105 |
+
"pad_token": "<pad>",
|
106 |
+
"unk_token": "<unk>"
|
107 |
+
}
|
tokenizer/spiece.model
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
|
3 |
+
size 791656
|
tokenizer/tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer/tokenizer_config.json
ADDED
@@ -0,0 +1,939 @@
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|
1 |
+
{
|
2 |
+
"add_prefix_space": null,
|
3 |
+
"added_tokens_decoder": {
|
4 |
+
"0": {
|
5 |
+
"content": "<pad>",
|
6 |
+
"lstrip": false,
|
7 |
+
"normalized": false,
|
8 |
+
"rstrip": false,
|
9 |
+
"single_word": false,
|
10 |
+
"special": true
|
11 |
+
},
|
12 |
+
"1": {
|
13 |
+
"content": "</s>",
|
14 |
+
"lstrip": false,
|
15 |
+
"normalized": false,
|
16 |
+
"rstrip": false,
|
17 |
+
"single_word": false,
|
18 |
+
"special": true
|
19 |
+
},
|
20 |
+
"2": {
|
21 |
+
"content": "<unk>",
|
22 |
+
"lstrip": false,
|
23 |
+
"normalized": false,
|
24 |
+
"rstrip": false,
|
25 |
+
"single_word": false,
|
26 |
+
"special": true
|
27 |
+
},
|
28 |
+
"32000": {
|
29 |
+
"content": "<extra_id_99>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
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"rstrip": false,
|
497 |
+
"single_word": false,
|
498 |
+
"special": true
|
499 |
+
},
|
500 |
+
"32059": {
|
501 |
+
"content": "<extra_id_40>",
|
502 |
+
"lstrip": false,
|
503 |
+
"normalized": false,
|
504 |
+
"rstrip": false,
|
505 |
+
"single_word": false,
|
506 |
+
"special": true
|
507 |
+
},
|
508 |
+
"32060": {
|
509 |
+
"content": "<extra_id_39>",
|
510 |
+
"lstrip": false,
|
511 |
+
"normalized": false,
|
512 |
+
"rstrip": false,
|
513 |
+
"single_word": false,
|
514 |
+
"special": true
|
515 |
+
},
|
516 |
+
"32061": {
|
517 |
+
"content": "<extra_id_38>",
|
518 |
+
"lstrip": false,
|
519 |
+
"normalized": false,
|
520 |
+
"rstrip": false,
|
521 |
+
"single_word": false,
|
522 |
+
"special": true
|
523 |
+
},
|
524 |
+
"32062": {
|
525 |
+
"content": "<extra_id_37>",
|
526 |
+
"lstrip": false,
|
527 |
+
"normalized": false,
|
528 |
+
"rstrip": false,
|
529 |
+
"single_word": false,
|
530 |
+
"special": true
|
531 |
+
},
|
532 |
+
"32063": {
|
533 |
+
"content": "<extra_id_36>",
|
534 |
+
"lstrip": false,
|
535 |
+
"normalized": false,
|
536 |
+
"rstrip": false,
|
537 |
+
"single_word": false,
|
538 |
+
"special": true
|
539 |
+
},
|
540 |
+
"32064": {
|
541 |
+
"content": "<extra_id_35>",
|
542 |
+
"lstrip": false,
|
543 |
+
"normalized": false,
|
544 |
+
"rstrip": false,
|
545 |
+
"single_word": false,
|
546 |
+
"special": true
|
547 |
+
},
|
548 |
+
"32065": {
|
549 |
+
"content": "<extra_id_34>",
|
550 |
+
"lstrip": false,
|
551 |
+
"normalized": false,
|
552 |
+
"rstrip": false,
|
553 |
+
"single_word": false,
|
554 |
+
"special": true
|
555 |
+
},
|
556 |
+
"32066": {
|
557 |
+
"content": "<extra_id_33>",
|
558 |
+
"lstrip": false,
|
559 |
+
"normalized": false,
|
560 |
+
"rstrip": false,
|
561 |
+
"single_word": false,
|
562 |
+
"special": true
|
563 |
+
},
|
564 |
+
"32067": {
|
565 |
+
"content": "<extra_id_32>",
|
566 |
+
"lstrip": false,
|
567 |
+
"normalized": false,
|
568 |
+
"rstrip": false,
|
569 |
+
"single_word": false,
|
570 |
+
"special": true
|
571 |
+
},
|
572 |
+
"32068": {
|
573 |
+
"content": "<extra_id_31>",
|
574 |
+
"lstrip": false,
|
575 |
+
"normalized": false,
|
576 |
+
"rstrip": false,
|
577 |
+
"single_word": false,
|
578 |
+
"special": true
|
579 |
+
},
|
580 |
+
"32069": {
|
581 |
+
"content": "<extra_id_30>",
|
582 |
+
"lstrip": false,
|
583 |
+
"normalized": false,
|
584 |
+
"rstrip": false,
|
585 |
+
"single_word": false,
|
586 |
+
"special": true
|
587 |
+
},
|
588 |
+
"32070": {
|
589 |
+
"content": "<extra_id_29>",
|
590 |
+
"lstrip": false,
|
591 |
+
"normalized": false,
|
592 |
+
"rstrip": false,
|
593 |
+
"single_word": false,
|
594 |
+
"special": true
|
595 |
+
},
|
596 |
+
"32071": {
|
597 |
+
"content": "<extra_id_28>",
|
598 |
+
"lstrip": false,
|
599 |
+
"normalized": false,
|
600 |
+
"rstrip": false,
|
601 |
+
"single_word": false,
|
602 |
+
"special": true
|
603 |
+
},
|
604 |
+
"32072": {
|
605 |
+
"content": "<extra_id_27>",
|
606 |
+
"lstrip": false,
|
607 |
+
"normalized": false,
|
608 |
+
"rstrip": false,
|
609 |
+
"single_word": false,
|
610 |
+
"special": true
|
611 |
+
},
|
612 |
+
"32073": {
|
613 |
+
"content": "<extra_id_26>",
|
614 |
+
"lstrip": false,
|
615 |
+
"normalized": false,
|
616 |
+
"rstrip": false,
|
617 |
+
"single_word": false,
|
618 |
+
"special": true
|
619 |
+
},
|
620 |
+
"32074": {
|
621 |
+
"content": "<extra_id_25>",
|
622 |
+
"lstrip": false,
|
623 |
+
"normalized": false,
|
624 |
+
"rstrip": false,
|
625 |
+
"single_word": false,
|
626 |
+
"special": true
|
627 |
+
},
|
628 |
+
"32075": {
|
629 |
+
"content": "<extra_id_24>",
|
630 |
+
"lstrip": false,
|
631 |
+
"normalized": false,
|
632 |
+
"rstrip": false,
|
633 |
+
"single_word": false,
|
634 |
+
"special": true
|
635 |
+
},
|
636 |
+
"32076": {
|
637 |
+
"content": "<extra_id_23>",
|
638 |
+
"lstrip": false,
|
639 |
+
"normalized": false,
|
640 |
+
"rstrip": false,
|
641 |
+
"single_word": false,
|
642 |
+
"special": true
|
643 |
+
},
|
644 |
+
"32077": {
|
645 |
+
"content": "<extra_id_22>",
|
646 |
+
"lstrip": false,
|
647 |
+
"normalized": false,
|
648 |
+
"rstrip": false,
|
649 |
+
"single_word": false,
|
650 |
+
"special": true
|
651 |
+
},
|
652 |
+
"32078": {
|
653 |
+
"content": "<extra_id_21>",
|
654 |
+
"lstrip": false,
|
655 |
+
"normalized": false,
|
656 |
+
"rstrip": false,
|
657 |
+
"single_word": false,
|
658 |
+
"special": true
|
659 |
+
},
|
660 |
+
"32079": {
|
661 |
+
"content": "<extra_id_20>",
|
662 |
+
"lstrip": false,
|
663 |
+
"normalized": false,
|
664 |
+
"rstrip": false,
|
665 |
+
"single_word": false,
|
666 |
+
"special": true
|
667 |
+
},
|
668 |
+
"32080": {
|
669 |
+
"content": "<extra_id_19>",
|
670 |
+
"lstrip": false,
|
671 |
+
"normalized": false,
|
672 |
+
"rstrip": false,
|
673 |
+
"single_word": false,
|
674 |
+
"special": true
|
675 |
+
},
|
676 |
+
"32081": {
|
677 |
+
"content": "<extra_id_18>",
|
678 |
+
"lstrip": false,
|
679 |
+
"normalized": false,
|
680 |
+
"rstrip": false,
|
681 |
+
"single_word": false,
|
682 |
+
"special": true
|
683 |
+
},
|
684 |
+
"32082": {
|
685 |
+
"content": "<extra_id_17>",
|
686 |
+
"lstrip": false,
|
687 |
+
"normalized": false,
|
688 |
+
"rstrip": false,
|
689 |
+
"single_word": false,
|
690 |
+
"special": true
|
691 |
+
},
|
692 |
+
"32083": {
|
693 |
+
"content": "<extra_id_16>",
|
694 |
+
"lstrip": false,
|
695 |
+
"normalized": false,
|
696 |
+
"rstrip": false,
|
697 |
+
"single_word": false,
|
698 |
+
"special": true
|
699 |
+
},
|
700 |
+
"32084": {
|
701 |
+
"content": "<extra_id_15>",
|
702 |
+
"lstrip": false,
|
703 |
+
"normalized": false,
|
704 |
+
"rstrip": false,
|
705 |
+
"single_word": false,
|
706 |
+
"special": true
|
707 |
+
},
|
708 |
+
"32085": {
|
709 |
+
"content": "<extra_id_14>",
|
710 |
+
"lstrip": false,
|
711 |
+
"normalized": false,
|
712 |
+
"rstrip": false,
|
713 |
+
"single_word": false,
|
714 |
+
"special": true
|
715 |
+
},
|
716 |
+
"32086": {
|
717 |
+
"content": "<extra_id_13>",
|
718 |
+
"lstrip": false,
|
719 |
+
"normalized": false,
|
720 |
+
"rstrip": false,
|
721 |
+
"single_word": false,
|
722 |
+
"special": true
|
723 |
+
},
|
724 |
+
"32087": {
|
725 |
+
"content": "<extra_id_12>",
|
726 |
+
"lstrip": false,
|
727 |
+
"normalized": false,
|
728 |
+
"rstrip": false,
|
729 |
+
"single_word": false,
|
730 |
+
"special": true
|
731 |
+
},
|
732 |
+
"32088": {
|
733 |
+
"content": "<extra_id_11>",
|
734 |
+
"lstrip": false,
|
735 |
+
"normalized": false,
|
736 |
+
"rstrip": false,
|
737 |
+
"single_word": false,
|
738 |
+
"special": true
|
739 |
+
},
|
740 |
+
"32089": {
|
741 |
+
"content": "<extra_id_10>",
|
742 |
+
"lstrip": false,
|
743 |
+
"normalized": false,
|
744 |
+
"rstrip": false,
|
745 |
+
"single_word": false,
|
746 |
+
"special": true
|
747 |
+
},
|
748 |
+
"32090": {
|
749 |
+
"content": "<extra_id_9>",
|
750 |
+
"lstrip": false,
|
751 |
+
"normalized": false,
|
752 |
+
"rstrip": false,
|
753 |
+
"single_word": false,
|
754 |
+
"special": true
|
755 |
+
},
|
756 |
+
"32091": {
|
757 |
+
"content": "<extra_id_8>",
|
758 |
+
"lstrip": false,
|
759 |
+
"normalized": false,
|
760 |
+
"rstrip": false,
|
761 |
+
"single_word": false,
|
762 |
+
"special": true
|
763 |
+
},
|
764 |
+
"32092": {
|
765 |
+
"content": "<extra_id_7>",
|
766 |
+
"lstrip": false,
|
767 |
+
"normalized": false,
|
768 |
+
"rstrip": false,
|
769 |
+
"single_word": false,
|
770 |
+
"special": true
|
771 |
+
},
|
772 |
+
"32093": {
|
773 |
+
"content": "<extra_id_6>",
|
774 |
+
"lstrip": false,
|
775 |
+
"normalized": false,
|
776 |
+
"rstrip": false,
|
777 |
+
"single_word": false,
|
778 |
+
"special": true
|
779 |
+
},
|
780 |
+
"32094": {
|
781 |
+
"content": "<extra_id_5>",
|
782 |
+
"lstrip": false,
|
783 |
+
"normalized": false,
|
784 |
+
"rstrip": false,
|
785 |
+
"single_word": false,
|
786 |
+
"special": true
|
787 |
+
},
|
788 |
+
"32095": {
|
789 |
+
"content": "<extra_id_4>",
|
790 |
+
"lstrip": false,
|
791 |
+
"normalized": false,
|
792 |
+
"rstrip": false,
|
793 |
+
"single_word": false,
|
794 |
+
"special": true
|
795 |
+
},
|
796 |
+
"32096": {
|
797 |
+
"content": "<extra_id_3>",
|
798 |
+
"lstrip": false,
|
799 |
+
"normalized": false,
|
800 |
+
"rstrip": false,
|
801 |
+
"single_word": false,
|
802 |
+
"special": true
|
803 |
+
},
|
804 |
+
"32097": {
|
805 |
+
"content": "<extra_id_2>",
|
806 |
+
"lstrip": false,
|
807 |
+
"normalized": false,
|
808 |
+
"rstrip": false,
|
809 |
+
"single_word": false,
|
810 |
+
"special": true
|
811 |
+
},
|
812 |
+
"32098": {
|
813 |
+
"content": "<extra_id_1>",
|
814 |
+
"lstrip": false,
|
815 |
+
"normalized": false,
|
816 |
+
"rstrip": false,
|
817 |
+
"single_word": false,
|
818 |
+
"special": true
|
819 |
+
},
|
820 |
+
"32099": {
|
821 |
+
"content": "<extra_id_0>",
|
822 |
+
"lstrip": false,
|
823 |
+
"normalized": false,
|
824 |
+
"rstrip": false,
|
825 |
+
"single_word": false,
|
826 |
+
"special": true
|
827 |
+
}
|
828 |
+
},
|
829 |
+
"additional_special_tokens": [
|
830 |
+
"<extra_id_0>",
|
831 |
+
"<extra_id_1>",
|
832 |
+
"<extra_id_2>",
|
833 |
+
"<extra_id_3>",
|
834 |
+
"<extra_id_4>",
|
835 |
+
"<extra_id_5>",
|
836 |
+
"<extra_id_6>",
|
837 |
+
"<extra_id_7>",
|
838 |
+
"<extra_id_8>",
|
839 |
+
"<extra_id_9>",
|
840 |
+
"<extra_id_10>",
|
841 |
+
"<extra_id_11>",
|
842 |
+
"<extra_id_12>",
|
843 |
+
"<extra_id_13>",
|
844 |
+
"<extra_id_14>",
|
845 |
+
"<extra_id_15>",
|
846 |
+
"<extra_id_16>",
|
847 |
+
"<extra_id_17>",
|
848 |
+
"<extra_id_18>",
|
849 |
+
"<extra_id_19>",
|
850 |
+
"<extra_id_20>",
|
851 |
+
"<extra_id_21>",
|
852 |
+
"<extra_id_22>",
|
853 |
+
"<extra_id_23>",
|
854 |
+
"<extra_id_24>",
|
855 |
+
"<extra_id_25>",
|
856 |
+
"<extra_id_26>",
|
857 |
+
"<extra_id_27>",
|
858 |
+
"<extra_id_28>",
|
859 |
+
"<extra_id_29>",
|
860 |
+
"<extra_id_30>",
|
861 |
+
"<extra_id_31>",
|
862 |
+
"<extra_id_32>",
|
863 |
+
"<extra_id_33>",
|
864 |
+
"<extra_id_34>",
|
865 |
+
"<extra_id_35>",
|
866 |
+
"<extra_id_36>",
|
867 |
+
"<extra_id_37>",
|
868 |
+
"<extra_id_38>",
|
869 |
+
"<extra_id_39>",
|
870 |
+
"<extra_id_40>",
|
871 |
+
"<extra_id_41>",
|
872 |
+
"<extra_id_42>",
|
873 |
+
"<extra_id_43>",
|
874 |
+
"<extra_id_44>",
|
875 |
+
"<extra_id_45>",
|
876 |
+
"<extra_id_46>",
|
877 |
+
"<extra_id_47>",
|
878 |
+
"<extra_id_48>",
|
879 |
+
"<extra_id_49>",
|
880 |
+
"<extra_id_50>",
|
881 |
+
"<extra_id_51>",
|
882 |
+
"<extra_id_52>",
|
883 |
+
"<extra_id_53>",
|
884 |
+
"<extra_id_54>",
|
885 |
+
"<extra_id_55>",
|
886 |
+
"<extra_id_56>",
|
887 |
+
"<extra_id_57>",
|
888 |
+
"<extra_id_58>",
|
889 |
+
"<extra_id_59>",
|
890 |
+
"<extra_id_60>",
|
891 |
+
"<extra_id_61>",
|
892 |
+
"<extra_id_62>",
|
893 |
+
"<extra_id_63>",
|
894 |
+
"<extra_id_64>",
|
895 |
+
"<extra_id_65>",
|
896 |
+
"<extra_id_66>",
|
897 |
+
"<extra_id_67>",
|
898 |
+
"<extra_id_68>",
|
899 |
+
"<extra_id_69>",
|
900 |
+
"<extra_id_70>",
|
901 |
+
"<extra_id_71>",
|
902 |
+
"<extra_id_72>",
|
903 |
+
"<extra_id_73>",
|
904 |
+
"<extra_id_74>",
|
905 |
+
"<extra_id_75>",
|
906 |
+
"<extra_id_76>",
|
907 |
+
"<extra_id_77>",
|
908 |
+
"<extra_id_78>",
|
909 |
+
"<extra_id_79>",
|
910 |
+
"<extra_id_80>",
|
911 |
+
"<extra_id_81>",
|
912 |
+
"<extra_id_82>",
|
913 |
+
"<extra_id_83>",
|
914 |
+
"<extra_id_84>",
|
915 |
+
"<extra_id_85>",
|
916 |
+
"<extra_id_86>",
|
917 |
+
"<extra_id_87>",
|
918 |
+
"<extra_id_88>",
|
919 |
+
"<extra_id_89>",
|
920 |
+
"<extra_id_90>",
|
921 |
+
"<extra_id_91>",
|
922 |
+
"<extra_id_92>",
|
923 |
+
"<extra_id_93>",
|
924 |
+
"<extra_id_94>",
|
925 |
+
"<extra_id_95>",
|
926 |
+
"<extra_id_96>",
|
927 |
+
"<extra_id_97>",
|
928 |
+
"<extra_id_98>",
|
929 |
+
"<extra_id_99>"
|
930 |
+
],
|
931 |
+
"clean_up_tokenization_spaces": false,
|
932 |
+
"eos_token": "</s>",
|
933 |
+
"extra_ids": 100,
|
934 |
+
"extra_special_tokens": {},
|
935 |
+
"model_max_length": 1000000000000000019884624838656,
|
936 |
+
"pad_token": "<pad>",
|
937 |
+
"tokenizer_class": "T5Tokenizer",
|
938 |
+
"unk_token": "<unk>"
|
939 |
+
}
|
tokenizer_config.json
ADDED
@@ -0,0 +1,939 @@
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1 |
+
{
|
2 |
+
"add_prefix_space": null,
|
3 |
+
"added_tokens_decoder": {
|
4 |
+
"0": {
|
5 |
+
"content": "<pad>",
|
6 |
+
"lstrip": false,
|
7 |
+
"normalized": false,
|
8 |
+
"rstrip": false,
|
9 |
+
"single_word": false,
|
10 |
+
"special": true
|
11 |
+
},
|
12 |
+
"1": {
|
13 |
+
"content": "</s>",
|
14 |
+
"lstrip": false,
|
15 |
+
"normalized": false,
|
16 |
+
"rstrip": false,
|
17 |
+
"single_word": false,
|
18 |
+
"special": true
|
19 |
+
},
|
20 |
+
"2": {
|
21 |
+
"content": "<unk>",
|
22 |
+
"lstrip": false,
|
23 |
+
"normalized": false,
|
24 |
+
"rstrip": false,
|
25 |
+
"single_word": false,
|
26 |
+
"special": true
|
27 |
+
},
|
28 |
+
"32000": {
|
29 |
+
"content": "<extra_id_99>",
|
30 |
+
"lstrip": false,
|
31 |
+
"normalized": false,
|
32 |
+
"rstrip": false,
|
33 |
+
"single_word": false,
|
34 |
+
"special": true
|
35 |
+
},
|
36 |
+
"32001": {
|
37 |
+
"content": "<extra_id_98>",
|
38 |
+
"lstrip": false,
|
39 |
+
"normalized": false,
|
40 |
+
"rstrip": false,
|
41 |
+
"single_word": false,
|
42 |
+
"special": true
|
43 |
+
},
|
44 |
+
"32002": {
|
45 |
+
"content": "<extra_id_97>",
|
46 |
+
"lstrip": false,
|
47 |
+
"normalized": false,
|
48 |
+
"rstrip": false,
|
49 |
+
"single_word": false,
|
50 |
+
"special": true
|
51 |
+
},
|
52 |
+
"32003": {
|
53 |
+
"content": "<extra_id_96>",
|
54 |
+
"lstrip": false,
|
55 |
+
"normalized": false,
|
56 |
+
"rstrip": false,
|
57 |
+
"single_word": false,
|
58 |
+
"special": true
|
59 |
+
},
|
60 |
+
"32004": {
|
61 |
+
"content": "<extra_id_95>",
|
62 |
+
"lstrip": false,
|
63 |
+
"normalized": false,
|
64 |
+
"rstrip": false,
|
65 |
+
"single_word": false,
|
66 |
+
"special": true
|
67 |
+
},
|
68 |
+
"32005": {
|
69 |
+
"content": "<extra_id_94>",
|
70 |
+
"lstrip": false,
|
71 |
+
"normalized": false,
|
72 |
+
"rstrip": false,
|
73 |
+
"single_word": false,
|
74 |
+
"special": true
|
75 |
+
},
|
76 |
+
"32006": {
|
77 |
+
"content": "<extra_id_93>",
|
78 |
+
"lstrip": false,
|
79 |
+
"normalized": false,
|
80 |
+
"rstrip": false,
|
81 |
+
"single_word": false,
|
82 |
+
"special": true
|
83 |
+
},
|
84 |
+
"32007": {
|
85 |
+
"content": "<extra_id_92>",
|
86 |
+
"lstrip": false,
|
87 |
+
"normalized": false,
|
88 |
+
"rstrip": false,
|
89 |
+
"single_word": false,
|
90 |
+
"special": true
|
91 |
+
},
|
92 |
+
"32008": {
|
93 |
+
"content": "<extra_id_91>",
|
94 |
+
"lstrip": false,
|
95 |
+
"normalized": false,
|
96 |
+
"rstrip": false,
|
97 |
+
"single_word": false,
|
98 |
+
"special": true
|
99 |
+
},
|
100 |
+
"32009": {
|
101 |
+
"content": "<extra_id_90>",
|
102 |
+
"lstrip": false,
|
103 |
+
"normalized": false,
|
104 |
+
"rstrip": false,
|
105 |
+
"single_word": false,
|
106 |
+
"special": true
|
107 |
+
},
|
108 |
+
"32010": {
|
109 |
+
"content": "<extra_id_89>",
|
110 |
+
"lstrip": false,
|
111 |
+
"normalized": false,
|
112 |
+
"rstrip": false,
|
113 |
+
"single_word": false,
|
114 |
+
"special": true
|
115 |
+
},
|
116 |
+
"32011": {
|
117 |
+
"content": "<extra_id_88>",
|
118 |
+
"lstrip": false,
|
119 |
+
"normalized": false,
|
120 |
+
"rstrip": false,
|
121 |
+
"single_word": false,
|
122 |
+
"special": true
|
123 |
+
},
|
124 |
+
"32012": {
|
125 |
+
"content": "<extra_id_87>",
|
126 |
+
"lstrip": false,
|
127 |
+
"normalized": false,
|
128 |
+
"rstrip": false,
|
129 |
+
"single_word": false,
|
130 |
+
"special": true
|
131 |
+
},
|
132 |
+
"32013": {
|
133 |
+
"content": "<extra_id_86>",
|
134 |
+
"lstrip": false,
|
135 |
+
"normalized": false,
|
136 |
+
"rstrip": false,
|
137 |
+
"single_word": false,
|
138 |
+
"special": true
|
139 |
+
},
|
140 |
+
"32014": {
|
141 |
+
"content": "<extra_id_85>",
|
142 |
+
"lstrip": false,
|
143 |
+
"normalized": false,
|
144 |
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train_results.json
ADDED
@@ -0,0 +1,8 @@
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{
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trainer_state.json
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@@ -0,0 +1,352 @@
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+
"wi_0",
|
16 |
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"wi_1",
|
17 |
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"wo"
|
18 |
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]
|
19 |
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},
|
20 |
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|
21 |
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"output_dir": "./medical-qa-t5-lora",
|
22 |
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|
23 |
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|
24 |
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|
25 |
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|
26 |
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|
27 |
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|
28 |
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|
29 |
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|
30 |
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|
31 |
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|
32 |
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|
33 |
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"evaluation_strategy": "steps",
|
34 |
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|
35 |
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|
36 |
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"dataloader_num_workers": 4,
|
37 |
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"remove_unused_columns": false,
|
38 |
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"load_best_model_at_end": true,
|
39 |
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"metric_for_best_model": "eval_loss",
|
40 |
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"greater_is_better": false,
|
41 |
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"report_to": "tensorboard",
|
42 |
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"logging_dir": "./logs",
|
43 |
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|
44 |
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"seed": 42
|
45 |
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},
|
46 |
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"data": {
|
47 |
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"dataset_name": "keivalya/MedQuad-MedicalQnADataset",
|
48 |
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"train_split": "train",
|
49 |
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"validation_split": "validation",
|
50 |
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"test_split": "test",
|
51 |
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"question_prefix": "medical question: ",
|
52 |
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"answer_prefix": "medical answer: ",
|
53 |
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"max_samples": null,
|
54 |
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|
55 |
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"lowercase": false,
|
56 |
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|
57 |
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},
|
58 |
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"huggingface": {
|
59 |
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"hub_model_id": "Adilbai/medical-qa-t5-lora",
|
60 |
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"hub_token": null,
|
61 |
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"push_to_hub": true,
|
62 |
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"hub_private_repo": false,
|
63 |
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|
64 |
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"save_lora_adapter": true,
|
65 |
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"save_tokenizer": true,
|
66 |
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"save_config": true
|
67 |
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},
|
68 |
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"device": "cuda",
|
69 |
+
"cache_dir": "./cache",
|
70 |
+
"data_dir": "./data"
|
71 |
+
}
|