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SA-roberta-e3-w2-1-b16-w0.01-data2
YanJiangJerry/SA-roberta-e3-w2-1-b16-w0.01-data2
SA-roberta-e3-w2-1-b16-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
- 2699adde
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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-w2-1-b16-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: 0.5272
- Accuracy: 0.9032
- F1: 0.8664
- Precision: 0.8924
- Recall: 0.8418
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 |
|---|---|---|---|---|---|---|---|
| 0.2717 | 1.0 | 581 | 0.3400 | 0.9132 | 0.8811 | 0.9003 | 0.8627 |
| 0.1102 | 2.0 | 1162 | 0.5082 | 0.9021 | 0.8706 | 0.8580 | 0.8836 |
| 0.0525 | 3.0 | 1743 | 0.5272 | 0.9032 | 0.8664 | 0.8924 | 0.8418 |
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