safetensors generated_from_trainer base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: results
  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. -->

# results

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: 0.6218

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.9667        | 0.07  | 500   | 0.8561          |
| 0.8253        | 0.14  | 1000  | 0.7976          |
| 0.7771        | 0.2   | 1500  | 0.7676          |
| 0.7623        | 0.27  | 2000  | 0.7459          |
| 0.7399        | 0.34  | 2500  | 0.7269          |
| 0.7253        | 0.41  | 3000  | 0.7166          |
| 0.7241        | 0.47  | 3500  | 0.7035          |
| 0.7063        | 0.54  | 4000  | 0.6962          |
| 0.6857        | 0.61  | 4500  | 0.6883          |
| 0.6909        | 0.68  | 5000  | 0.6829          |
| 0.6754        | 0.75  | 5500  | 0.6731          |
| 0.6803        | 0.81  | 6000  | 0.6657          |
| 0.6659        | 0.88  | 6500  | 0.6599          |
| 0.6603        | 0.95  | 7000  | 0.6556          |
| 0.6249        | 1.02  | 7500  | 0.6610          |
| 0.53          | 1.09  | 8000  | 0.6583          |
| 0.5246        | 1.15  | 8500  | 0.6544          |
| 0.5204        | 1.22  | 9000  | 0.6515          |
| 0.5135        | 1.29  | 9500  | 0.6498          |
| 0.5165        | 1.36  | 10000 | 0.6433          |
| 0.518         | 1.42  | 10500 | 0.6410          |
| 0.5032        | 1.49  | 11000 | 0.6368          |
| 0.5091        | 1.56  | 11500 | 0.6335          |
| 0.5038        | 1.63  | 12000 | 0.6307          |
| 0.4907        | 1.7   | 12500 | 0.6302          |
| 0.5006        | 1.76  | 13000 | 0.6262          |
| 0.4823        | 1.83  | 13500 | 0.6239          |
| 0.4906        | 1.9   | 14000 | 0.6225          |
| 0.4905        | 1.97  | 14500 | 0.6218          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
