---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: mistral_7b_cosine_lr
  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. -->

# mistral_7b_cosine_lr

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3993

## 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: 0.003
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 15
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 11.1885       | 0.0549 | 10   | 61.4970         |
| 37.6512       | 0.1098 | 20   | 12.9405         |
| 14.576        | 0.1647 | 30   | 27.9852         |
| 9.5892        | 0.2196 | 40   | 6.4722          |
| 7.7639        | 0.2745 | 50   | 6.8158          |
| 6.3878        | 0.3294 | 60   | 6.3811          |
| 6.6118        | 0.3844 | 70   | 5.9281          |
| 6.006         | 0.4393 | 80   | 5.6753          |
| 6.1011        | 0.4942 | 90   | 5.8083          |
| 5.7396        | 0.5491 | 100  | 5.6193          |
| 5.5128        | 0.6040 | 110  | 5.4848          |
| 5.4599        | 0.6589 | 120  | 5.4267          |
| 5.5193        | 0.7138 | 130  | 5.4757          |
| 5.4488        | 0.7687 | 140  | 5.4422          |
| 5.4257        | 0.8236 | 150  | 5.3845          |
| 5.3938        | 0.8785 | 160  | 5.3727          |
| 5.3937        | 0.9334 | 170  | 5.3646          |
| 5.3916        | 0.9883 | 180  | 5.4825          |
| 5.4217        | 1.0432 | 190  | 5.3534          |
| 5.3915        | 1.0981 | 200  | 5.3497          |
| 5.3656        | 1.1531 | 210  | 5.3416          |
| 5.3718        | 1.2080 | 220  | 5.3691          |
| 5.3763        | 1.2629 | 230  | 5.4102          |
| 5.4039        | 1.3178 | 240  | 5.3993          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0