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---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: lambda-llama-3-8b-dpo-test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lambda-llama-3-8b-dpo-test
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5772
- Rewards/chosen: -1.0430
- Rewards/rejected: -1.6270
- Rewards/accuracies: 0.7063
- Rewards/margins: 0.5841
- Logps/rejected: -558.6804
- Logps/chosen: -509.0577
- Logits/rejected: -2.5324
- Logits/chosen: -2.3779
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6351 | 0.2093 | 100 | 0.6359 | -0.6754 | -0.9179 | 0.6746 | 0.2426 | -487.7697 | -472.2982 | -2.4565 | -2.2922 |
| 0.6101 | 0.4186 | 200 | 0.5990 | -0.7996 | -1.1966 | 0.7143 | 0.3970 | -515.6393 | -484.7244 | -2.4477 | -2.2933 |
| 0.5738 | 0.6279 | 300 | 0.5819 | -1.0722 | -1.6607 | 0.7143 | 0.5885 | -562.0454 | -511.9821 | -2.5003 | -2.3506 |
| 0.5808 | 0.8373 | 400 | 0.5776 | -1.0426 | -1.6196 | 0.7063 | 0.5769 | -557.9310 | -509.0269 | -2.6060 | -2.4454 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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