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FoRC_S1_BERT
ThuyNT03/FoRC_S1_BERT
FoRC_S1_BERT is a text classification model from ThuyNT03. Use it when you need a label for a piece of text. 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
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Feb 1, 2024
- Updated
- Feb 3, 2024
- SHA
- e53fa112
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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. -->
FoRC_S1_BERT
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: 1.3170
- Accuracy: 0.6476
- F1: 0.6317
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.0182 | 2.0 | 2596 | 1.4831 | 0.6049 | 0.5673 |
| 1.1498 | 4.0 | 5192 | 1.3217 | 0.6439 | 0.6224 |
| 0.8597 | 6.0 | 7788 | 1.3170 | 0.6476 | 0.6317 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 1, 2024
- Updated
- Feb 3, 2024