---
library_name: peft
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: mistral_cot_simplest_qlora
  results: []
---

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

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7150

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8904        | 1.0   | 3    | 0.8287          |
| 1.4592        | 2.0   | 6    | 0.7422          |
| 1.4592        | 3.0   | 9    | 0.7162          |
| 1.0477        | 3.4   | 10   | 0.7150          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.1.2
- Datasets 3.2.0
- Tokenizers 0.21.0