my_Ws_extraction_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2355
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9570
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 3 | 1.4172 | 0.0526 | 0.0833 | 0.0645 | 0.9083 |
| No log | 2.0 | 6 | 1.2355 | 0.0 | 0.0 | 0.0 | 0.9570 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.2
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Model tree for manimaranpa07/my_Ws_extraction_model
Base model
distilbert/distilbert-base-uncased