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---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: SChem5Labels-mistralai-Mistral-7B-v0.1-inter-dataset-frequency-model-pairwise-mse-cycle1
  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. -->

# SChem5Labels-mistralai-Mistral-7B-v0.1-inter-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: 0.4913

## 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: 1
- eval_batch_size: 1
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0618        | 0.02  | 69   | 1.0339          |
| 0.7935        | 1.02  | 138  | 0.7594          |
| 0.5315        | 2.02  | 207  | 0.5753          |
| 0.4378        | 3.02  | 276  | 0.4896          |
| 0.388         | 4.02  | 345  | 0.4429          |
| 0.3829        | 5.02  | 414  | 0.4113          |
| 0.3528        | 6.02  | 483  | 0.4034          |
| 0.3329        | 7.02  | 552  | 0.3958          |
| 0.3117        | 8.02  | 621  | 0.3946          |
| 0.3141        | 9.02  | 690  | 0.3906          |
| 0.2732        | 10.02 | 759  | 0.3971          |
| 0.2638        | 11.02 | 828  | 0.4242          |
| 0.2313        | 12.02 | 897  | 0.4540          |
| 0.1666        | 13.02 | 966  | 0.4913          |


### Framework versions

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