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banglabert-bert-finetuned-ner
This model is a fine-tuned version of csebuetnlp/banglabert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9526
- Precision: 0.0143
- Recall: 0.0769
- F1: 0.0241
- Accuracy: 0.0143
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 2.0085 | 0.0143 | 0.0769 | 0.0241 | 0.0143 |
| No log | 2.0 | 2 | 1.9711 | 0.0143 | 0.0769 | 0.0241 | 0.0143 |
| No log | 3.0 | 3 | 1.9526 | 0.0143 | 0.0769 | 0.0241 | 0.0143 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
