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bert_for_prof_roles_128_all_labels
AndrewDOrlov/bert_for_prof_roles_128_all_labels
bert_for_prof_roles_128_all_labels 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 22, 2024
- Updated
- May 22, 2024
- SHA
- 7d6312d9
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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_128_all_labels
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0059
- F1: 0.8558
- Roc Auc: 0.9126
- Accuracy: 0.8233
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 |
|---|---|---|---|---|---|---|
| 0.0119 | 1.0 | 7016 | 0.0108 | 0.7427 | 0.8192 | 0.6327 |
| 0.0076 | 2.0 | 14032 | 0.0077 | 0.8118 | 0.8790 | 0.7549 |
| 0.006 | 3.0 | 21048 | 0.0067 | 0.8352 | 0.8958 | 0.7874 |
| 0.005 | 4.0 | 28064 | 0.0062 | 0.8459 | 0.9058 | 0.8074 |
| 0.0046 | 5.0 | 35080 | 0.0060 | 0.8525 | 0.9112 | 0.8190 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- May 22, 2024
- Updated
- May 22, 2024