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# token_classification_test

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2740
- Precision: 0.9257
- Recall: 0.9158
- F1: 0.9207
- Accuracy: 0.9354

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 47   | 1.1923          | 0.6932    | 0.6053 | 0.6463 | 0.7206   |
| No log        | 2.0   | 94   | 0.6271          | 0.8247    | 0.7896 | 0.8068 | 0.8400   |
| No log        | 3.0   | 141  | 0.4480          | 0.8799    | 0.8512 | 0.8653 | 0.8918   |
| No log        | 4.0   | 188  | 0.3751          | 0.8996    | 0.8744 | 0.8868 | 0.9088   |
| No log        | 5.0   | 235  | 0.3377          | 0.9043    | 0.8882 | 0.8962 | 0.9155   |
| No log        | 6.0   | 282  | 0.3139          | 0.9150    | 0.8976 | 0.9062 | 0.9223   |
| No log        | 7.0   | 329  | 0.3060          | 0.9091    | 0.8972 | 0.9031 | 0.9214   |
| No log        | 8.0   | 376  | 0.2918          | 0.9162    | 0.9064 | 0.9113 | 0.9271   |
| No log        | 9.0   | 423  | 0.2856          | 0.9209    | 0.9070 | 0.9139 | 0.9293   |
| No log        | 10.0  | 470  | 0.2809          | 0.9228    | 0.9081 | 0.9154 | 0.9311   |
| 0.5294        | 11.0  | 517  | 0.2803          | 0.9232    | 0.9104 | 0.9168 | 0.9321   |
| 0.5294        | 12.0  | 564  | 0.2761          | 0.9259    | 0.9154 | 0.9206 | 0.9349   |
| 0.5294        | 13.0  | 611  | 0.2737          | 0.9272    | 0.9156 | 0.9214 | 0.9357   |
| 0.5294        | 14.0  | 658  | 0.2742          | 0.9279    | 0.9164 | 0.9221 | 0.9362   |
| 0.5294        | 15.0  | 705  | 0.2740          | 0.9257    | 0.9158 | 0.9207 | 0.9354   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "token_classification_test", "results": []}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us