---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: mistralit2_1000_STEPS_5e8_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. -->

# mistralit2_1000_STEPS_5e8_SFT_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: 0.3690

## 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: 5e-08
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4484        | 0.1   | 50   | 1.4370          |
| 1.3055        | 0.2   | 100  | 1.2880          |
| 1.1102        | 0.29  | 150  | 1.0868          |
| 0.9133        | 0.39  | 200  | 0.8993          |
| 0.7102        | 0.49  | 250  | 0.6891          |
| 0.5453        | 0.59  | 300  | 0.5207          |
| 0.4238        | 0.68  | 350  | 0.4248          |
| 0.4008        | 0.78  | 400  | 0.3916          |
| 0.3768        | 0.88  | 450  | 0.3790          |
| 0.3766        | 0.98  | 500  | 0.3744          |
| 0.3672        | 1.07  | 550  | 0.3718          |
| 0.3752        | 1.17  | 600  | 0.3702          |
| 0.3828        | 1.27  | 650  | 0.3694          |
| 0.3502        | 1.37  | 700  | 0.3691          |
| 0.3676        | 1.46  | 750  | 0.3690          |
| 0.3717        | 1.56  | 800  | 0.3690          |
| 0.3695        | 1.66  | 850  | 0.3690          |
| 0.3727        | 1.76  | 900  | 0.3690          |
| 0.3854        | 1.86  | 950  | 0.3690          |
| 0.3768        | 1.95  | 1000 | 0.3690          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2