Training complete
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README.md
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---
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base_model: csebuetnlp/banglabert
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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
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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: 0.7540530477530749
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- name: Recall
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type: recall
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value: 0.7567416940049906
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- name: F1
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type: f1
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value: 0.7553949784896273
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- name: Accuracy
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type: accuracy
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value: 0.8181902034079325
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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
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This model is a fine-tuned version of [csebuetnlp/banglabert](https://huggingface.co/csebuetnlp/banglabert) on the pos_tag_100k dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6322
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- Precision: 0.7541
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- Recall: 0.7567
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- F1: 0.7554
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- Accuracy: 0.8182
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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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| 0.7003 | 1.0 | 20000 | 0.6762 | 0.7281 | 0.7339 | 0.7310 | 0.8000 |
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| 0.6097 | 2.0 | 40000 | 0.6277 | 0.7481 | 0.7481 | 0.7481 | 0.8135 |
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| 0.5062 | 3.0 | 60000 | 0.6322 | 0.7541 | 0.7567 | 0.7554 | 0.8182 |
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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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