transformers safetensors mistral text-generation trl dpo generated_from_trainer base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: 400STEPS_1e7rate_01beta_T5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 400STEPS_1e7rate_01beta_T5

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6483
- Rewards/chosen: -0.0026
- Rewards/rejected: -0.1019
- Rewards/accuracies: 0.6593
- Rewards/margins: 0.0994
- Logps/rejected: -15.7387
- Logps/chosen: -12.9908
- Logits/rejected: -3.1652
- Logits/chosen: -3.1650

## 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-07
- 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: 400

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6916        | 0.1   | 50   | 0.6908          | 0.0048         | 0.0002           | 0.5670             | 0.0047          | -14.7176       | -12.9168     | -3.1591         | -3.1588       |
| 0.6821        | 0.2   | 100  | 0.6764          | 0.0187         | -0.0159          | 0.6681             | 0.0346          | -14.8782       | -12.7778     | -3.1625         | -3.1622       |
| 0.6647        | 0.29  | 150  | 0.6629          | 0.0225         | -0.0422          | 0.6659             | 0.0648          | -15.1414       | -12.7399     | -3.1625         | -3.1623       |
| 0.6536        | 0.39  | 200  | 0.6552          | 0.0148         | -0.0679          | 0.6505             | 0.0827          | -15.3987       | -12.8175     | -3.1657         | -3.1654       |
| 0.6354        | 0.49  | 250  | 0.6509          | 0.0022         | -0.0909          | 0.6593             | 0.0931          | -15.6282       | -12.9431     | -3.1646         | -3.1643       |
| 0.6468        | 0.59  | 300  | 0.6484          | -0.0022        | -0.1013          | 0.6527             | 0.0991          | -15.7319       | -12.9869     | -3.1653         | -3.1650       |
| 0.6549        | 0.68  | 350  | 0.6481          | -0.0021        | -0.1019          | 0.6571             | 0.0998          | -15.7386       | -12.9865     | -3.1652         | -3.1650       |
| 0.6684        | 0.78  | 400  | 0.6483          | -0.0026        | -0.1019          | 0.6593             | 0.0994          | -15.7387       | -12.9908     | -3.1652         | -3.1650       |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.0+cu117
- Datasets 2.17.0
- Tokenizers 0.15.1
