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Appearance-classifier-with-ratings
lengocquangLAB/Appearance-classifier-with-ratings
Appearance-classifier-with-ratings is a text classification model from lengocquangLAB. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 11, 2024
- Updated
- Apr 12, 2024
- SHA
- 3fceec34
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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. -->
Appearance-classifier-with-ratings
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5312
- Accuracy: 0.4029
- Recall: 0.4029
- Precision: 0.4029
- F1: 0.4029
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-05
- 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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 1.4455 | 1.0 | 5000 | 1.4442 | 0.3914 | 0.3914 | 0.3914 | 0.3914 |
| 1.3156 | 2.0 | 10000 | 1.4637 | 0.3976 | 0.3976 | 0.3976 | 0.3976 |
| 1.1218 | 3.0 | 15000 | 1.5312 | 0.4029 | 0.4029 | 0.4029 | 0.4029 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Apr 11, 2024
- Updated
- Apr 12, 2024