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---
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
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