---
license: apache-2.0
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: cognitivecomputations/dolphin-2.1-mistral-7b
model-index:
- name: doplhin-dpo-1-epoch
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# doplhin-dpo-1-epoch

This model is a fine-tuned version of [cognitivecomputations/dolphin-2.1-mistral-7b](https://huggingface.co/cognitivecomputations/dolphin-2.1-mistral-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6046
- Rewards/chosen: -6.6173
- Rewards/rejected: -10.5237
- Rewards/accuracies: 0.7880
- Rewards/margins: 3.9064
- Logps/rejected: -431.3049
- Logps/chosen: -422.0936
- Logits/rejected: -2.5993
- Logits/chosen: -2.6739

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 0.9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5544        | 0.62  | 700  | 0.6046          | -6.6173        | -10.5237         | 0.7880             | 3.9064          | -431.3049      | -422.0936    | -2.5993         | -2.6739       |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.2