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--- |
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license: cc-by-4.0 |
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base_model: pythainlp/thainer-corpus-v2-base-model |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lst20 |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: toneza |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: lst20 |
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type: lst20 |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.768370802562324 |
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- name: Recall |
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type: recall |
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value: 0.8120041393583994 |
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- name: F1 |
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type: f1 |
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value: 0.7895851240015932 |
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- name: Accuracy |
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type: accuracy |
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value: 0.956478116244312 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# toneza |
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This model is a fine-tuned version of [pythainlp/thainer-corpus-v2-base-model](https://huggingface.co/pythainlp/thainer-corpus-v2-base-model) on the lst20 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1293 |
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- Precision: 0.7684 |
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- Recall: 0.8120 |
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- F1: 0.7896 |
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- Accuracy: 0.9565 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.1226 | 1.0 | 1978 | 0.1416 | 0.7414 | 0.7802 | 0.7603 | 0.9518 | |
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| 0.098 | 2.0 | 3956 | 0.1324 | 0.7602 | 0.7966 | 0.7780 | 0.9545 | |
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| 0.0895 | 3.0 | 5934 | 0.1293 | 0.7684 | 0.8120 | 0.7896 | 0.9565 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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