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--- |
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base_model: mHossain/bengali_pos_v1_300000 |
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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_400000 |
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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: 0.7830405270513077 |
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- name: Recall |
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type: recall |
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value: 0.7856186076789224 |
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- name: F1 |
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type: f1 |
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value: 0.7843274488361194 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8402036064122549 |
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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_400000 |
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This model is a fine-tuned version of [mHossain/bengali_pos_v1_300000](https://huggingface.co/mHossain/bengali_pos_v1_300000) on the pos_tag_100k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5609 |
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- Precision: 0.7830 |
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- Recall: 0.7856 |
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- F1: 0.7843 |
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- Accuracy: 0.8402 |
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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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| 0.5908 | 1.0 | 22500 | 0.5513 | 0.7688 | 0.7698 | 0.7693 | 0.8289 | |
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| 0.4642 | 2.0 | 45000 | 0.5415 | 0.7799 | 0.7822 | 0.7810 | 0.8382 | |
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| 0.3773 | 3.0 | 67500 | 0.5609 | 0.7830 | 0.7856 | 0.7843 | 0.8402 | |
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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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