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my_awesome_wnut_model
Saitk/my_awesome_wnut_model
my_awesome_wnut_model is a token classification model from Saitk. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jan 13, 2025
- Updated
- Jan 13, 2025
- SHA
- 6a132971
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
my_awesome_wnut_model
This model is a fine-tuned version of distilbert/distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0770
- Precision: 0.9083
- Recall: 0.8423
- F1: 0.8741
- Accuracy: 0.9790
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 118 | 0.1285 | 0.8468 | 0.5851 | 0.6920 | 0.9557 |
| No log | 2.0 | 236 | 0.0904 | 0.8260 | 0.7780 | 0.8013 | 0.9673 |
| No log | 3.0 | 354 | 0.0837 | 0.8756 | 0.7739 | 0.8216 | 0.9714 |
| No log | 4.0 | 472 | 0.0796 | 0.8810 | 0.7988 | 0.8379 | 0.9738 |
| 0.1058 | 5.0 | 590 | 0.0780 | 0.9106 | 0.8029 | 0.8534 | 0.9762 |
| 0.1058 | 6.0 | 708 | 0.0738 | 0.9036 | 0.8361 | 0.8685 | 0.9782 |
| 0.1058 | 7.0 | 826 | 0.0744 | 0.9 | 0.8402 | 0.8691 | 0.9784 |
| 0.1058 | 8.0 | 944 | 0.0761 | 0.9002 | 0.8423 | 0.8703 | 0.9782 |
| 0.0232 | 9.0 | 1062 | 0.0766 | 0.9067 | 0.8465 | 0.8755 | 0.9791 |
| 0.0232 | 10.0 | 1180 | 0.0770 | 0.9083 | 0.8423 | 0.8741 | 0.9790 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cpu
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 13, 2025
- Updated
- Jan 13, 2025