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-3.3.1-Mistral-7b-Multilanguage-3.1.0
  results: []
---

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# ZeroShot-3.3.1-Mistral-7b-Multilanguage-3.1.0

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: 0.3819

## 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: 8
- eval_batch_size: 2
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7016        | 0.03  | 50   | 0.6892          |
| 0.53          | 0.06  | 100  | 0.5066          |
| 0.4652        | 0.09  | 150  | 0.4579          |
| 0.4299        | 0.12  | 200  | 0.4434          |
| 0.4337        | 0.16  | 250  | 0.4362          |
| 0.4213        | 0.19  | 300  | 0.4306          |
| 0.4207        | 0.22  | 350  | 0.4242          |
| 0.4161        | 0.25  | 400  | 0.4199          |
| 0.418         | 0.28  | 450  | 0.4170          |
| 0.4           | 0.31  | 500  | 0.4134          |
| 0.4119        | 0.34  | 550  | 0.4105          |
| 0.3993        | 0.37  | 600  | 0.4075          |
| 0.394         | 0.4   | 650  | 0.4048          |
| 0.389         | 0.43  | 700  | 0.4023          |
| 0.391         | 0.47  | 750  | 0.4004          |
| 0.4052        | 0.5   | 800  | 0.3978          |
| 0.3817        | 0.53  | 850  | 0.3960          |
| 0.3781        | 0.56  | 900  | 0.3940          |
| 0.3889        | 0.59  | 950  | 0.3920          |
| 0.3923        | 0.62  | 1000 | 0.3902          |
| 0.3759        | 0.65  | 1050 | 0.3891          |
| 0.3825        | 0.68  | 1100 | 0.3878          |
| 0.3832        | 0.71  | 1150 | 0.3863          |
| 0.3726        | 0.74  | 1200 | 0.3851          |
| 0.3826        | 0.78  | 1250 | 0.3844          |
| 0.3822        | 0.81  | 1300 | 0.3836          |
| 0.3764        | 0.84  | 1350 | 0.3829          |
| 0.385         | 0.87  | 1400 | 0.3824          |
| 0.3755        | 0.9   | 1450 | 0.3821          |
| 0.3621        | 0.93  | 1500 | 0.3820          |
| 0.3749        | 0.96  | 1550 | 0.3819          |
| 0.3778        | 0.99  | 1600 | 0.3819          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2