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output
jhonalevc1995/output
output is a text classification model from jhonalevc1995. 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
- Sep 20, 2024
- Updated
- Sep 21, 2024
- SHA
- 8512aa59
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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. -->
output
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0837
- Accuracy: 0.9865
- Precision: 0.9937
- Recall: 0.9809
- F1: 0.9873
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: 8
- eval_batch_size: 8
- seed: 0
- 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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0168 | 0.1380 | 250 | 0.0997 | 0.9851 | 0.9841 | 0.9881 | 0.9861 |
| 0.1 | 0.2759 | 500 | 0.0789 | 0.9873 | 0.9897 | 0.9866 | 0.9881 |
| 0.0522 | 0.4139 | 750 | 0.0811 | 0.9870 | 0.9861 | 0.9897 | 0.9879 |
| 0.1133 | 0.5519 | 1000 | 0.0837 | 0.9865 | 0.9937 | 0.9809 | 0.9873 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 20, 2024
- Updated
- Sep 21, 2024