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DataSnipper_FinerDistilBert_FullSequence
gvisser/DataSnipper_FinerDistilBert_FullSequence
DataSnipper_FinerDistilBert_FullSequence is a token classification model from gvisser. 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
- Feb 14, 2024
- Updated
- Feb 14, 2024
- SHA
- fdd9778c
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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. -->
DataSnipper_FinerDistilBert_FullSequence
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0913
- Precision: 0.8606
- Recall: 0.8141
- F1: 0.8367
- Accuracy: 0.9170
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: 1e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0108 | 1.0 | 56274 | 0.1081 | 0.7908 | 0.7278 | 0.7580 | 0.8778 |
| 0.0082 | 2.0 | 112548 | 0.0950 | 0.8250 | 0.7870 | 0.8056 | 0.9022 |
| 0.0066 | 3.0 | 168822 | 0.0893 | 0.8471 | 0.7902 | 0.8177 | 0.9065 |
| 0.0052 | 4.0 | 225096 | 0.0898 | 0.8585 | 0.8107 | 0.8339 | 0.9160 |
| 0.0043 | 5.0 | 281370 | 0.0913 | 0.8606 | 0.8141 | 0.8367 | 0.9170 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 14, 2024
- Updated
- Feb 14, 2024