---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: mistral-json-finetune
  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-json-finetune

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3730

## 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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2986        | 0.57  | 50   | 0.6897          |
| 0.4469        | 1.14  | 100  | 0.4239          |
| 0.2978        | 1.71  | 150  | 0.3497          |
| 0.2279        | 2.29  | 200  | 0.3126          |
| 0.1869        | 2.86  | 250  | 0.2858          |
| 0.137         | 3.43  | 300  | 0.2848          |
| 0.1221        | 4.0   | 350  | 0.2713          |
| 0.0918        | 4.57  | 400  | 0.2750          |
| 0.0832        | 5.14  | 450  | 0.2781          |
| 0.0681        | 5.71  | 500  | 0.2807          |
| 0.055         | 6.29  | 550  | 0.2902          |
| 0.0515        | 6.86  | 600  | 0.2746          |
| 0.0463        | 7.43  | 650  | 0.3078          |
| 0.0421        | 8.0   | 700  | 0.2971          |
| 0.0354        | 8.57  | 750  | 0.3196          |
| 0.0276        | 9.14  | 800  | 0.3490          |
| 0.0281        | 9.71  | 850  | 0.3411          |
| 0.026         | 10.29 | 900  | 0.3658          |
| 0.0241        | 10.86 | 950  | 0.3661          |
| 0.0209        | 11.43 | 1000 | 0.3730          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0