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SA-roberta-e3-w1-2.5-b16-mt4-w0.01-data2
YanJiangJerry/SA-roberta-e3-w1-2.5-b16-mt4-w0.01-data2
SA-roberta-e3-w1-2.5-b16-mt4-w0.01-data2 is a text classification model from YanJiangJerry. 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
- roberta
- Access
- Public
- Created
- Jul 14, 2023
- Updated
- Jul 14, 2023
- SHA
- 767ec21a
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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. -->
SA-roberta-e3-w1-2.5-b16-mt4-w0.01-data2
This model is a fine-tuned version of Amalq/autotrain-smm4h_large_roberta_clean-874027878 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6606
- Accuracy: 0.9088
- F1: 0.875
- Precision: 0.8941
- Recall: 0.8567
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: 16
- eval_batch_size: 16
- seed: 42
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2898 | 1.0 | 581 | 0.5149 | 0.9221 | 0.8930 | 0.9154 | 0.8716 |
| 0.1117 | 2.0 | 1162 | 0.7317 | 0.9010 | 0.8633 | 0.8892 | 0.8388 |
| 0.0536 | 3.0 | 1743 | 0.6606 | 0.9088 | 0.875 | 0.8941 | 0.8567 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Jul 14, 2023
- Updated
- Jul 14, 2023