---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: mistral-7B-Instruct-prompt
  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-Instruct-prompt

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: 0.0962

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.745         | 0.75  | 100  | 0.8404          |
| 0.5396        | 1.5   | 200  | 0.6313          |
| 0.3702        | 2.26  | 300  | 0.4994          |
| 0.3676        | 3.01  | 400  | 0.4106          |
| 0.3623        | 3.76  | 500  | 0.3409          |
| 0.2239        | 4.51  | 600  | 0.2893          |
| 0.1719        | 5.26  | 700  | 0.2405          |
| 0.1971        | 6.02  | 800  | 0.1866          |
| 0.1446        | 6.77  | 900  | 0.1591          |
| 0.1066        | 7.52  | 1000 | 0.1381          |
| 0.0866        | 8.27  | 1100 | 0.1193          |
| 0.0701        | 9.02  | 1200 | 0.1061          |
| 0.0641        | 9.77  | 1300 | 0.1017          |
| 0.0511        | 10.53 | 1400 | 0.0958          |
| 0.0407        | 11.28 | 1500 | 0.0963          |
| 0.0332        | 12.03 | 1600 | 0.0938          |
| 0.0268        | 12.78 | 1700 | 0.0952          |
| 0.0251        | 13.53 | 1800 | 0.0961          |
| 0.023         | 14.29 | 1900 | 0.0961          |
| 0.0219        | 15.04 | 2000 | 0.0962          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2