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BERT_0_350
xhorvat9/BERT_0_350
BERT_0_350 is a text classification model from xhorvat9. 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
- Mar 29, 2023
- Updated
- Mar 29, 2023
- SHA
- 739788cd
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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. -->
output
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5522
- Accuracy: 0.8706
- Precision: 0.9221
- Recall: 0.8285
- F1: 0.8728
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2351 | 0.49 | 500 | 0.4091 | 0.8641 | 0.8835 | 0.8596 | 0.8714 |
| 0.206 | 0.98 | 1000 | 0.4545 | 0.8594 | 0.9210 | 0.8068 | 0.8601 |
| 0.1315 | 1.47 | 1500 | 0.5653 | 0.8660 | 0.8769 | 0.8722 | 0.8745 |
| 0.1503 | 1.96 | 2000 | 0.5522 | 0.8706 | 0.9221 | 0.8285 | 0.8728 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 29, 2023
- Updated
- Mar 29, 2023