---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Na_M2_1000steps_1e6rate_SFT
  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. -->

# Na_M2_1000steps_1e6rate_SFT

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: 0.1550

## 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-06
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.349         | 0.2667 | 50   | 0.3425          |
| 0.2797        | 0.5333 | 100  | 0.2671          |
| 0.1882        | 0.8    | 150  | 0.1831          |
| 0.1593        | 1.0667 | 200  | 0.1748          |
| 0.1609        | 1.3333 | 250  | 0.1586          |
| 0.1544        | 1.6    | 300  | 0.1575          |
| 0.1558        | 1.8667 | 350  | 0.1564          |
| 0.1524        | 2.1333 | 400  | 0.1574          |
| 0.1527        | 2.4    | 450  | 0.1568          |
| 0.1564        | 2.6667 | 500  | 0.1554          |
| 0.1523        | 2.9333 | 550  | 0.1563          |
| 0.1519        | 3.2    | 600  | 0.1558          |
| 0.1532        | 3.4667 | 650  | 0.1555          |
| 0.1508        | 3.7333 | 700  | 0.1549          |
| 0.1518        | 4.0    | 750  | 0.1550          |
| 0.1507        | 4.2667 | 800  | 0.1551          |
| 0.1501        | 4.5333 | 850  | 0.1550          |
| 0.1477        | 4.8    | 900  | 0.1549          |
| 0.1464        | 5.0667 | 950  | 0.1550          |
| 0.1488        | 5.3333 | 1000 | 0.1550          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1