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roberta-base-finetuned-classification-v2
ThomasLI/roberta-base-finetuned-classification-v2
roberta-base-finetuned-classification-v2 is a text classification model from ThomasLI. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Mar 8, 2023
- Updated
- Mar 8, 2023
- SHA
- 93532e8c
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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. -->
roberta-base-finetuned-classification-v2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4137
- Accuracy: 0.8638
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-06
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 200 | 0.4706 | 0.7638 |
| No log | 2.0 | 400 | 0.3843 | 0.84 |
| 0.4541 | 3.0 | 600 | 0.3669 | 0.8588 |
| 0.4541 | 4.0 | 800 | 0.4570 | 0.8438 |
| 0.2003 | 5.0 | 1000 | 0.4137 | 0.8638 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Mar 8, 2023
- Updated
- Mar 8, 2023