---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: mistralit2_500_STEPS_1e8_rate_03_beta_DPO
  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. -->

# mistralit2_500_STEPS_1e8_rate_03_beta_DPO

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6903
- Rewards/chosen: -0.0048
- Rewards/rejected: -0.0113
- Rewards/accuracies: 0.5121
- Rewards/margins: 0.0065
- Logps/rejected: -28.6101
- Logps/chosen: -23.4018
- Logits/rejected: -2.8650
- Logits/chosen: -2.8653

## 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: 1e-08
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6911        | 0.1   | 50   | 0.6909          | 0.0027         | -0.0025          | 0.4967             | 0.0052          | -28.5807       | -23.3768     | -2.8653         | -2.8655       |
| 0.6916        | 0.2   | 100  | 0.6928          | -0.0010        | -0.0023          | 0.4571             | 0.0014          | -28.5802       | -23.3891     | -2.8653         | -2.8655       |
| 0.6931        | 0.29  | 150  | 0.6916          | -0.0047        | -0.0087          | 0.4659             | 0.0040          | -28.6014       | -23.4015     | -2.8652         | -2.8654       |
| 0.6922        | 0.39  | 200  | 0.6914          | -0.0046        | -0.0090          | 0.4681             | 0.0044          | -28.6024       | -23.4011     | -2.8651         | -2.8654       |
| 0.6921        | 0.49  | 250  | 0.6927          | -0.0086        | -0.0103          | 0.4747             | 0.0017          | -28.6067       | -23.4145     | -2.8651         | -2.8653       |
| 0.6938        | 0.59  | 300  | 0.6916          | -0.0092        | -0.0132          | 0.4835             | 0.0040          | -28.6163       | -23.4163     | -2.8651         | -2.8654       |
| 0.6976        | 0.68  | 350  | 0.6907          | -0.0058        | -0.0116          | 0.4747             | 0.0058          | -28.6111       | -23.4052     | -2.8651         | -2.8654       |
| 0.6918        | 0.78  | 400  | 0.6902          | -0.0069        | -0.0137          | 0.4967             | 0.0068          | -28.6182       | -23.4089     | -2.8651         | -2.8653       |
| 0.6862        | 0.88  | 450  | 0.6903          | -0.0048        | -0.0113          | 0.5121             | 0.0065          | -28.6101       | -23.4018     | -2.8650         | -2.8653       |
| 0.6946        | 0.98  | 500  | 0.6903          | -0.0048        | -0.0113          | 0.5121             | 0.0065          | -28.6101       | -23.4018     | -2.8650         | -2.8653       |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2