Text Classification
Transformers
Safetensors
English
deberta
anli
natural-language-inference
sequence-classification
Eval Results (legacy)
Instructions to use Lidor-Mashiach/deberta-large-anli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lidor-Mashiach/deberta-large-anli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lidor-Mashiach/deberta-large-anli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Lidor-Mashiach/deberta-large-anli") model = AutoModelForSequenceClassification.from_pretrained("Lidor-Mashiach/deberta-large-anli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_card.json from Lidor-Mashiach/deberta-large-anli: direct link, hf CLI and curl.
- Browser
- Download file 942 Bytes
-
https://huggingface.co/Lidor-Mashiach/deberta-large-anli/resolve/main/model_card.json
- Command line
-
hf download hf://Lidor-Mashiach/deberta-large-anli/model_card.json
-
curl -L -o model_card.json https://huggingface.co/Lidor-Mashiach/deberta-large-anli/resolve/main/model_card.json
942 Bytes
| { | |
| "model": "DeBERTa-large", | |
| "dataset": "ANLI", | |
| "backbone": "microsoft/deberta-large", | |
| "run_seed": 1299843651, | |
| "validation_accuracy": 0.6221875, | |
| "training": { | |
| "epochs": 3, | |
| "batch_size": 16, | |
| "gradient_accumulation_steps": 2, | |
| "learning_rate": 1.6958369168519958e-05, | |
| "weight_decay": 0.1, | |
| "warmup_ratio": 0.1828387398995507, | |
| "label_smoothing_factor": 0.1, | |
| "adam_beta2": 0.999, | |
| "adam_epsilon": 1e-08, | |
| "max_grad_norm": 1.0, | |
| "max_seq_len": 128, | |
| "fp16": "auto", | |
| "amp": "fp32" | |
| }, | |
| "baseline_eval": { | |
| "validation_accuracy": 0.6221875, | |
| "test_accuracy": 0.6178125, | |
| "validation_examples": 3200, | |
| "test_examples": 3200, | |
| "validation_split": "dev", | |
| "test_split": "test" | |
| }, | |
| "repository": "Lidor-Mashiach/deberta-large-anli", | |
| "license": "cc-by-nc-4.0", | |
| "base_model_license": "mit", | |
| "training_data": "facebook/anli", | |
| "training_data_license": "cc-by-nc-4.0" | |
| } | |