---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: v1_1000_STEPS_1e5_SFT_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. -->

# v1_1000_STEPS_1e5_SFT_SFT

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3149

## 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-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4004        | 0.05  | 50   | 0.4035          |
| 0.3957        | 0.1   | 100  | 0.4218          |
| 0.4548        | 0.15  | 150  | 0.4199          |
| 0.4488        | 0.2   | 200  | 0.3899          |
| 0.396         | 0.24  | 250  | 0.3871          |
| 0.3959        | 0.29  | 300  | 0.3832          |
| 0.3765        | 0.34  | 350  | 0.3775          |
| 0.3696        | 0.39  | 400  | 0.3704          |
| 0.3753        | 0.44  | 450  | 0.3608          |
| 0.3661        | 0.49  | 500  | 0.3537          |
| 0.3438        | 0.54  | 550  | 0.3473          |
| 0.349         | 0.59  | 600  | 0.3409          |
| 0.326         | 0.64  | 650  | 0.3345          |
| 0.3137        | 0.68  | 700  | 0.3284          |
| 0.3134        | 0.73  | 750  | 0.3226          |
| 0.3246        | 0.78  | 800  | 0.3190          |
| 0.3316        | 0.83  | 850  | 0.3164          |
| 0.3035        | 0.88  | 900  | 0.3152          |
| 0.3062        | 0.93  | 950  | 0.3150          |
| 0.3234        | 0.98  | 1000 | 0.3149          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2