---
base_model: hllj/meta-math-mistral-vi-math
tags:
- generated_from_trainer
model-index:
- name: sft-metamath-mistral-7b-vi-v1
  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. -->

# sft-metamath-mistral-7b-vi-v1

This model is a fine-tuned version of [hllj/meta-math-mistral-vi-math](https://huggingface.co/hllj/meta-math-mistral-vi-math) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4947

## 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-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3128        | 0.26  | 500  | 0.5093          |
| 0.2751        | 1.07  | 1000 | 0.4884          |
| 0.2585        | 1.33  | 1500 | 0.4943          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.15.0