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--- |
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base_model: mHossain/bengali_pos_v1_200000 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pos_tag_100k |
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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: bengali_pos_v1_300000 |
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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: pos_tag_100k |
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type: pos_tag_100k |
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config: conll2003 |
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split: validation |
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args: conll2003 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7824197234815842 |
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- name: Recall |
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type: recall |
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value: 0.7854805341357909 |
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- name: F1 |
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type: f1 |
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value: 0.783947141194579 |
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- name: Accuracy |
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type: accuracy |
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value: 0.839060352367862 |
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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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# bengali_pos_v1_300000 |
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This model is a fine-tuned version of [mHossain/bengali_pos_v1_200000](https://huggingface.co/mHossain/bengali_pos_v1_200000) on the pos_tag_100k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6558 |
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- Precision: 0.7824 |
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- Recall: 0.7855 |
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- F1: 0.7839 |
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- Accuracy: 0.8391 |
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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: 8 |
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- eval_batch_size: 8 |
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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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| 0.3708 | 1.0 | 22500 | 0.6313 | 0.7688 | 0.7733 | 0.7711 | 0.8304 | |
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| 0.3099 | 2.0 | 45000 | 0.6491 | 0.7770 | 0.7789 | 0.7780 | 0.8353 | |
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| 0.3127 | 3.0 | 67500 | 0.6558 | 0.7824 | 0.7855 | 0.7839 | 0.8391 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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