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bert-term-importance-v1
nikmandava/bert-term-importance-v1
bert-term-importance-v1 is a token classification model from nikmandava. 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
- bert
- Access
- Public
- Created
- May 7, 2025
- Updated
- May 7, 2025
- SHA
- 581b108d
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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. -->
bert-term-importance-v1
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0024
- Mse: 0.0024
- Rmse: 0.0487
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 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Rmse |
|---|---|---|---|---|---|
| 0.0034 | 1.0 | 675 | 0.0036 | 0.0037 | 0.0605 |
| 0.0028 | 2.0 | 1350 | 0.0028 | 0.0028 | 0.0532 |
| 0.0036 | 3.0 | 2025 | 0.0028 | 0.0028 | 0.0530 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.5.1
- Tokenizers 0.21.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 7, 2025
- Updated
- May 7, 2025