End of training
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README.md
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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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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: token_classification_data_pythainlp
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results: []
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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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# token_classification_data_pythainlp
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1187
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- Precision: 0.8363
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- Recall: 0.8886
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- F1: 0.8616
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- Accuracy: 0.9734
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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: 16
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- eval_batch_size: 16
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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: 5
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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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| No log | 1.0 | 247 | 0.1026 | 0.8297 | 0.8810 | 0.8546 | 0.9736 |
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| No log | 2.0 | 494 | 0.1113 | 0.8250 | 0.8818 | 0.8524 | 0.9730 |
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| 0.0356 | 3.0 | 741 | 0.1131 | 0.8300 | 0.8852 | 0.8567 | 0.9726 |
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| 0.0356 | 4.0 | 988 | 0.1188 | 0.8307 | 0.8899 | 0.8593 | 0.9730 |
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| 0.02 | 5.0 | 1235 | 0.1187 | 0.8363 | 0.8886 | 0.8616 | 0.9734 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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model.safetensors
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