---
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_1e7_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_1e7_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: 0.3111

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9785        | 0.2667 | 50   | 1.8984          |
| 0.815         | 0.5333 | 100  | 0.6662          |
| 0.4371        | 0.8    | 150  | 0.4306          |
| 0.3721        | 1.0667 | 200  | 0.3807          |
| 0.3439        | 1.3333 | 250  | 0.3367          |
| 0.3251        | 1.6    | 300  | 0.3266          |
| 0.3215        | 1.8667 | 350  | 0.3233          |
| 0.3156        | 2.1333 | 400  | 0.3205          |
| 0.3124        | 2.4    | 450  | 0.3183          |
| 0.3165        | 2.6667 | 500  | 0.3161          |
| 0.3128        | 2.9333 | 550  | 0.3130          |
| 0.3093        | 3.2    | 600  | 0.3120          |
| 0.311         | 3.4667 | 650  | 0.3109          |
| 0.3073        | 3.7333 | 700  | 0.3112          |
| 0.306         | 4.0    | 750  | 0.3115          |
| 0.307         | 4.2667 | 800  | 0.3112          |
| 0.3052        | 4.5333 | 850  | 0.3111          |
| 0.3048        | 4.8    | 900  | 0.3105          |
| 0.3034        | 5.0667 | 950  | 0.3111          |
| 0.3057        | 5.3333 | 1000 | 0.3111          |


### Framework versions

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