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roberta-large-detect-dep-v3
Trong-Nghia/roberta-large-detect-dep-v3
roberta-large-detect-dep-v3 is a text classification model from Trong-Nghia. 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
- Jul 13, 2023
- Updated
- Jul 21, 2023
- SHA
- 40565aa5
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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. -->
roberta-large-detect-dep-v3
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6359
- Accuracy: 0.713
- F1: 0.7817
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|
| 0.6348 | 1.0 | 751 | 0.5414 | 0.769 | 0.8241 |
| 0.5428 | 2.0 | 1502 | 0.5873 | 0.733 | 0.8027 |
| 0.4829 | 3.0 | 2253 | 0.6359 | 0.713 | 0.7817 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jul 13, 2023
- Updated
- Jul 21, 2023