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Goodreads_Books_Reviews_Roberta_53
lilouuch/Goodreads_Books_Reviews_Roberta_53
Goodreads_Books_Reviews_Roberta_53 is a text classification model from lilouuch. 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
- Feb 13, 2023
- Updated
- Feb 13, 2023
- SHA
- 676de27a
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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. -->
Goodreads_Books_Reviews_Roberta_53
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8038
- F1: 0.6238
- Accuracy: 0.6614
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| 0.8378 | 1.0 | 25313 | 0.8197 | 0.6092 | 0.6538 |
| 0.7683 | 2.0 | 50626 | 0.8038 | 0.6238 | 0.6614 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Feb 13, 2023
- Updated
- Feb 13, 2023