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-3.3.20-Mistral-7b-Multilanguage-3.2.0
  results: []
---

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# ZeroShot-3.3.20-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: 0.3347

## 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: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5234        | 0.06  | 100  | 0.4902          |
| 0.4606        | 0.12  | 200  | 0.4453          |
| 0.4223        | 0.19  | 300  | 0.4323          |
| 0.4124        | 0.25  | 400  | 0.4239          |
| 0.4023        | 0.31  | 500  | 0.4136          |
| 0.3954        | 0.37  | 600  | 0.4068          |
| 0.3835        | 0.43  | 700  | 0.4009          |
| 0.3815        | 0.5   | 800  | 0.3953          |
| 0.3738        | 0.56  | 900  | 0.3917          |
| 0.3728        | 0.62  | 1000 | 0.3870          |
| 0.3846        | 0.68  | 1100 | 0.3816          |
| 0.3872        | 0.74  | 1200 | 0.3773          |
| 0.3823        | 0.81  | 1300 | 0.3739          |
| 0.362         | 0.87  | 1400 | 0.3700          |
| 0.3661        | 0.93  | 1500 | 0.3663          |
| 0.3572        | 0.99  | 1600 | 0.3628          |
| 0.3185        | 1.05  | 1700 | 0.3611          |
| 0.3133        | 1.12  | 1800 | 0.3571          |
| 0.3153        | 1.18  | 1900 | 0.3538          |
| 0.3144        | 1.24  | 2000 | 0.3513          |
| 0.3082        | 1.3   | 2100 | 0.3480          |
| 0.315         | 1.36  | 2200 | 0.3460          |
| 0.3062        | 1.43  | 2300 | 0.3433          |
| 0.305         | 1.49  | 2400 | 0.3417          |
| 0.3131        | 1.55  | 2500 | 0.3396          |
| 0.3049        | 1.61  | 2600 | 0.3380          |
| 0.2971        | 1.67  | 2700 | 0.3371          |
| 0.2983        | 1.74  | 2800 | 0.3360          |
| 0.2987        | 1.8   | 2900 | 0.3353          |
| 0.2998        | 1.86  | 3000 | 0.3350          |
| 0.3066        | 1.92  | 3100 | 0.3348          |
| 0.3004        | 1.98  | 3200 | 0.3347          |


### Framework versions

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