---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: v1_1000_STEPS_1e8_rate_01_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. -->

# v1_1000_STEPS_1e8_rate_01_beta_DPO

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6930
- Rewards/chosen: -0.0000
- Rewards/rejected: -0.0004
- Rewards/accuracies: 0.4571
- Rewards/margins: 0.0004
- Logps/rejected: -16.8832
- Logps/chosen: -15.2532
- Logits/rejected: -3.3537
- Logits/chosen: -3.3538

## 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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6937        | 0.05  | 50   | 0.6931          | -0.0004        | -0.0006          | 0.4813             | 0.0002          | -16.8854       | -15.2569     | -3.3537         | -3.3538       |
| 0.6934        | 0.1   | 100  | 0.6930          | 0.0001         | -0.0003          | 0.4879             | 0.0004          | -16.8825       | -15.2519     | -3.3538         | -3.3539       |
| 0.6945        | 0.15  | 150  | 0.6931          | -0.0002        | -0.0003          | 0.4725             | 0.0001          | -16.8826       | -15.2550     | -3.3538         | -3.3539       |
| 0.6945        | 0.2   | 200  | 0.6933          | -0.0003        | -0.0000          | 0.4396             | -0.0003         | -16.8800       | -15.2561     | -3.3537         | -3.3538       |
| 0.693         | 0.24  | 250  | 0.6933          | -0.0002        | 0.0000           | 0.4352             | -0.0002         | -16.8791       | -15.2548     | -3.3538         | -3.3539       |
| 0.6934        | 0.29  | 300  | 0.6930          | 0.0003         | -0.0001          | 0.4549             | 0.0004          | -16.8806       | -15.2500     | -3.3539         | -3.3540       |
| 0.6945        | 0.34  | 350  | 0.6931          | -0.0007        | -0.0007          | 0.4462             | 0.0001          | -16.8867       | -15.2596     | -3.3539         | -3.3539       |
| 0.6914        | 0.39  | 400  | 0.6933          | -0.0006        | -0.0004          | 0.4593             | -0.0002         | -16.8834       | -15.2590     | -3.3538         | -3.3538       |
| 0.693         | 0.44  | 450  | 0.6932          | -0.0001        | -0.0001          | 0.4396             | -0.0000         | -16.8802       | -15.2539     | -3.3537         | -3.3537       |
| 0.6937        | 0.49  | 500  | 0.6931          | -0.0002        | -0.0003          | 0.4484             | 0.0001          | -16.8827       | -15.2548     | -3.3538         | -3.3539       |
| 0.6918        | 0.54  | 550  | 0.6930          | -0.0001        | -0.0004          | 0.4791             | 0.0003          | -16.8834       | -15.2541     | -3.3537         | -3.3538       |
| 0.6926        | 0.59  | 600  | 0.6933          | -0.0005        | -0.0002          | 0.4505             | -0.0002         | -16.8820       | -15.2580     | -3.3537         | -3.3537       |
| 0.6922        | 0.64  | 650  | 0.6933          | -0.0003        | -0.0000          | 0.4549             | -0.0003         | -16.8796       | -15.2563     | -3.3538         | -3.3539       |
| 0.693         | 0.68  | 700  | 0.6931          | -0.0006        | -0.0007          | 0.4484             | 0.0001          | -16.8861       | -15.2589     | -3.3538         | -3.3539       |
| 0.6926        | 0.73  | 750  | 0.6928          | 0.0001         | -0.0006          | 0.4879             | 0.0007          | -16.8858       | -15.2520     | -3.3538         | -3.3539       |
| 0.693         | 0.78  | 800  | 0.6931          | -0.0004        | -0.0007          | 0.4923             | 0.0002          | -16.8861       | -15.2574     | -3.3538         | -3.3539       |
| 0.693         | 0.83  | 850  | 0.6930          | -0.0002        | -0.0005          | 0.4462             | 0.0003          | -16.8842       | -15.2548     | -3.3537         | -3.3538       |
| 0.6926        | 0.88  | 900  | 0.6930          | -0.0000        | -0.0004          | 0.4571             | 0.0004          | -16.8832       | -15.2532     | -3.3537         | -3.3538       |
| 0.6937        | 0.93  | 950  | 0.6930          | -0.0000        | -0.0004          | 0.4571             | 0.0004          | -16.8832       | -15.2532     | -3.3537         | -3.3538       |
| 0.6926        | 0.98  | 1000 | 0.6930          | -0.0000        | -0.0004          | 0.4571             | 0.0004          | -16.8832       | -15.2532     | -3.3537         | -3.3538       |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2