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UIT-VSFC-Bert-CLSModel-v1
haihuynh/UIT-VSFC-Bert-CLSModel-v1
UIT-VSFC-Bert-CLSModel-v1 is a text classification model from haihuynh. 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
- Jun 20, 2024
- Updated
- Jun 20, 2024
- SHA
- 8413add3
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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. -->
UIT-VSFC-Bert-CLSModel-v1
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2665
- Accuracy: 0.9078
- F1: 0.7420
- Precision: 0.8056
- Recall: 0.7168
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: 0.0003
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 90 | 0.3628 | 0.8768 | 0.5982 | 0.5855 | 0.6143 |
| No log | 2.0 | 180 | 0.2813 | 0.9065 | 0.7141 | 0.8098 | 0.6912 |
| No log | 3.0 | 270 | 0.2665 | 0.9078 | 0.7420 | 0.8056 | 0.7168 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 20, 2024
- Updated
- Jun 20, 2024