---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: mistral-customerSupport-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-customerSupport-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: 0.6550

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8511        | 0.03  | 25   | 1.0647          |
| 0.6109        | 0.06  | 50   | 1.0602          |
| 0.6824        | 0.09  | 75   | 1.0368          |
| 0.876         | 0.12  | 100  | 0.9630          |
| 0.9261        | 0.15  | 125  | 0.9391          |
| 0.8642        | 0.18  | 150  | 0.9180          |
| 0.8901        | 0.21  | 175  | 0.9037          |
| 0.9167        | 0.24  | 200  | 0.8685          |
| 0.8831        | 0.27  | 225  | 0.8505          |
| 0.7935        | 0.3   | 250  | 0.8341          |
| 0.8635        | 0.33  | 275  | 0.8203          |
| 0.7317        | 0.36  | 300  | 0.8052          |
| 0.7195        | 0.39  | 325  | 0.7996          |
| 0.8332        | 0.42  | 350  | 0.7847          |
| 0.799         | 0.44  | 375  | 0.7733          |
| 0.6985        | 0.47  | 400  | 0.7677          |
| 0.7192        | 0.5   | 425  | 0.7594          |
| 0.7391        | 0.53  | 450  | 0.7459          |
| 0.6792        | 0.56  | 475  | 0.7312          |
| 0.8249        | 0.59  | 500  | 0.7299          |
| 0.6745        | 0.62  | 525  | 0.7193          |
| 0.6625        | 0.65  | 550  | 0.7233          |
| 0.5941        | 0.68  | 575  | 0.7132          |
| 0.704         | 0.71  | 600  | 0.7072          |
| 0.636         | 0.74  | 625  | 0.7002          |
| 0.6401        | 0.77  | 650  | 0.6958          |
| 0.773         | 0.8   | 675  | 0.6876          |
| 0.5974        | 0.83  | 700  | 0.6840          |
| 0.6062        | 0.86  | 725  | 0.6729          |
| 0.5464        | 0.89  | 750  | 0.6664          |
| 0.6384        | 0.92  | 775  | 0.6633          |
| 0.6292        | 0.95  | 800  | 0.6594          |
| 0.6629        | 0.98  | 825  | 0.6564          |
| 0.6414        | 1.01  | 850  | 0.6524          |
| 0.4689        | 1.04  | 875  | 0.6549          |
| 0.3982        | 1.07  | 900  | 0.6627          |
| 0.4089        | 1.1   | 925  | 0.6583          |
| 0.4483        | 1.13  | 950  | 0.6566          |
| 0.429         | 1.16  | 975  | 0.6555          |
| 0.4088        | 1.19  | 1000 | 0.6550          |


### Framework versions

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