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# token_classification_data_pythainlp

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 247  | 0.1026          | 0.8297    | 0.8810 | 0.8546 | 0.9736   |
| No log        | 2.0   | 494  | 0.1113          | 0.8250    | 0.8818 | 0.8524 | 0.9730   |
| 0.0356        | 3.0   | 741  | 0.1131          | 0.8300    | 0.8852 | 0.8567 | 0.9726   |
| 0.0356        | 4.0   | 988  | 0.1188          | 0.8307    | 0.8899 | 0.8593 | 0.9730   |
| 0.02          | 5.0   | 1235 | 0.1187          | 0.8363    | 0.8886 | 0.8616 | 0.9734   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "pythainlp/thainer-corpus-v2-base-model", "model-index": [{"name": "token_classification_data_pythainlp", "results": []}]}
transformers tensorboard safetensors camembert token-classification generated_from_trainer base_model:pythainlp/thainer-corpus-v2-base-model license:cc-by-4.0 autotrain_compatible endpoints_compatible region:us