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: SBIC-mistralai-Mistral-7B-v0.1-intra-dataset-frequency-model-pairwise-mse-cycle1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SBIC-mistralai-Mistral-7B-v0.1-intra-dataset-frequency-model-pairwise-mse-cycle1

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: 0.5520

## 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: 0.0001
- 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
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4802        | 0.04  | 31   | 2.4091          |
| 2.2997        | 1.04  | 62   | 2.2583          |
| 2.1019        | 2.04  | 93   | 2.0836          |
| 1.8498        | 3.04  | 124  | 1.8917          |
| 1.6275        | 4.04  | 155  | 1.7154          |
| 1.4091        | 5.04  | 186  | 1.5379          |
| 1.2361        | 6.04  | 217  | 1.3779          |
| 1.087         | 7.04  | 248  | 1.2654          |
| 0.9664        | 8.04  | 279  | 1.1340          |
| 0.8312        | 9.04  | 310  | 1.0311          |
| 0.7554        | 10.04 | 341  | 0.9393          |
| 0.6873        | 11.04 | 372  | 0.8599          |
| 0.6292        | 12.04 | 403  | 0.7976          |
| 0.5822        | 13.04 | 434  | 0.7410          |
| 0.5453        | 14.04 | 465  | 0.6989          |
| 0.5115        | 15.04 | 496  | 0.6611          |
| 0.4778        | 16.04 | 527  | 0.6292          |
| 0.4527        | 17.04 | 558  | 0.6054          |
| 0.4474        | 18.04 | 589  | 0.5882          |
| 0.4285        | 19.04 | 620  | 0.5740          |
| 0.4193        | 20.04 | 651  | 0.5642          |
| 0.4061        | 21.04 | 682  | 0.5583          |
| 0.4044        | 22.04 | 713  | 0.5544          |
| 0.4           | 23.04 | 744  | 0.5524          |
| 0.4029        | 24.04 | 775  | 0.5520          |
| 0.3973        | 25.04 | 806  | 0.5520          |
| 0.3977        | 26.04 | 837  | 0.5520          |
| 0.3947        | 27.04 | 868  | 0.5520          |
| 0.3983        | 28.04 | 899  | 0.5520          |
| 0.3934        | 29.04 | 930  | 0.5520          |
| 0.3977        | 30.04 | 961  | 0.5520          |
| 0.4022        | 31.04 | 992  | 0.5520          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
