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bert_for_prof_roles_128_labels_below_100
AndrewDOrlov/bert_for_prof_roles_128_labels_below_100
bert_for_prof_roles_128_labels_below_100 is a text classification model from AndrewDOrlov. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 21, 2024
- Updated
- May 21, 2024
- SHA
- c70a3fa7
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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_for_prof_roles
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0087
- F1: 0.8710
- Roc Auc: 0.9264
- Accuracy: 0.8495
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.0137 | 1.0 | 6885 | 0.0133 | 0.7959 | 0.8698 | 0.7314 |
| 0.01 | 2.0 | 13770 | 0.0110 | 0.8311 | 0.8941 | 0.7832 |
| 0.0082 | 3.0 | 20655 | 0.0100 | 0.8487 | 0.9110 | 0.8142 |
| 0.0066 | 4.0 | 27540 | 0.0094 | 0.8585 | 0.9182 | 0.8337 |
| 0.0056 | 5.0 | 34425 | 0.0092 | 0.8636 | 0.9222 | 0.8398 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- May 21, 2024
- Updated
- May 21, 2024