peft safetensors mistral trl sft generated_from_trainer base_model:mistralai/Mistral-7B-Instruct-v0.2 license:apache-2.0 region:us
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: ZeroShot-3.3.30-Mistral-7b-Multilanguage-3.2.0
  results: []
---

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# ZeroShot-3.3.30-Mistral-7b-Multilanguage-3.2.0

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: 0.3229

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- 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_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5038        | 0.03  | 100  | 0.4736          |
| 0.4404        | 0.06  | 200  | 0.4333          |
| 0.4516        | 0.09  | 300  | 0.4242          |
| 0.4316        | 0.12  | 400  | 0.4219          |
| 0.4422        | 0.16  | 500  | 0.4095          |
| 0.413         | 0.19  | 600  | 0.4049          |
| 0.4114        | 0.22  | 700  | 0.3989          |
| 0.3963        | 0.25  | 800  | 0.3941          |
| 0.4056        | 0.28  | 900  | 0.3888          |
| 0.4105        | 0.31  | 1000 | 0.3860          |
| 0.3966        | 0.34  | 1100 | 0.3804          |
| 0.3588        | 0.37  | 1200 | 0.3778          |
| 0.3715        | 0.4   | 1300 | 0.3718          |
| 0.3589        | 0.43  | 1400 | 0.3679          |
| 0.364         | 0.47  | 1500 | 0.3641          |
| 0.3707        | 0.5   | 1600 | 0.3589          |
| 0.3714        | 0.53  | 1700 | 0.3551          |
| 0.3595        | 0.56  | 1800 | 0.3507          |
| 0.352         | 0.59  | 1900 | 0.3476          |
| 0.352         | 0.62  | 2000 | 0.3434          |
| 0.3425        | 0.65  | 2100 | 0.3397          |
| 0.3459        | 0.68  | 2200 | 0.3365          |
| 0.3387        | 0.71  | 2300 | 0.3334          |
| 0.3358        | 0.74  | 2400 | 0.3307          |
| 0.3456        | 0.78  | 2500 | 0.3287          |
| 0.3365        | 0.81  | 2600 | 0.3272          |
| 0.3304        | 0.84  | 2700 | 0.3255          |
| 0.3204        | 0.87  | 2800 | 0.3244          |
| 0.3429        | 0.9   | 2900 | 0.3236          |
| 0.3323        | 0.93  | 3000 | 0.3232          |
| 0.3284        | 0.96  | 3100 | 0.3229          |
| 0.3177        | 0.99  | 3200 | 0.3229          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2