
<!-- 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. -->

# copilot_relex_v1

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0139
- Accuracy: 0.0014
- F1: 0.0027
- Precision: 0.0014
- Recall: 1.0

## 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: 2e-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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 172  | 0.0372          | 0.0014   | 0.0027 | 0.0014    | 1.0    |
| No log        | 2.0   | 344  | 0.0159          | 0.0014   | 0.0027 | 0.0014    | 1.0    |
| 0.1035        | 3.0   | 516  | 0.0139          | 0.0014   | 0.0027 | 0.0014    | 1.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "microsoft/deberta-v3-small", "model-index": [{"name": "copilot_relex_v1", "results": []}]}
transformers tensorboard safetensors deberta-v2 text-classification generated_from_trainer base_model:microsoft/deberta-v3-small license:mit autotrain_compatible endpoints_compatible region:us