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--- |
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base_model: mHossain/bengali_pos_v1_400000 |
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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_500000 |
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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: 0.7579696797959762 |
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- name: Recall |
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type: recall |
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value: 0.7590989712664066 |
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- name: F1 |
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type: f1 |
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value: 0.7585339052142781 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8206361113872795 |
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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_500000 |
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This model is a fine-tuned version of [mHossain/bengali_pos_v1_400000](https://huggingface.co/mHossain/bengali_pos_v1_400000) on the pos_tag_100k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6169 |
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- Precision: 0.7580 |
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- Recall: 0.7591 |
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- F1: 0.7585 |
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- Accuracy: 0.8206 |
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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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| 0.6277 | 1.0 | 22500 | 0.6102 | 0.7441 | 0.7474 | 0.7458 | 0.8109 | |
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| 0.5143 | 2.0 | 45000 | 0.5998 | 0.7549 | 0.7561 | 0.7555 | 0.8183 | |
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| 0.4392 | 3.0 | 67500 | 0.6169 | 0.7580 | 0.7591 | 0.7585 | 0.8206 | |
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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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