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htk-aes-3
hoanghoavienvo/htk-aes-3
htk-aes-3 is a text classification model from hoanghoavienvo. 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
- Jun 6, 2024
- Updated
- Jun 6, 2024
- SHA
- 277960cf
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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. -->
htk-aes-3
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9541
- Qwk: 0.7743
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk |
|---|---|---|---|---|
| No log | 1.0 | 347 | 1.0461 | 0.6401 |
| 1.1175 | 2.0 | 694 | 0.9818 | 0.6984 |
| 0.8755 | 3.0 | 1041 | 0.9005 | 0.7652 |
| 0.8755 | 4.0 | 1388 | 0.9128 | 0.7657 |
| 0.8081 | 5.0 | 1735 | 1.0008 | 0.7390 |
| 0.7673 | 6.0 | 2082 | 0.9348 | 0.7652 |
| 0.7673 | 7.0 | 2429 | 0.9025 | 0.7775 |
| 0.7218 | 8.0 | 2776 | 0.9945 | 0.7643 |
| 0.6966 | 9.0 | 3123 | 0.9992 | 0.7588 |
| 0.6966 | 10.0 | 3470 | 0.9541 | 0.7743 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jun 6, 2024
- Updated
- Jun 6, 2024