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bert-base-uncased-clasificator-emotions
ValenHumano/bert-base-uncased-clasificator-emotions
bert-base-uncased-clasificator-emotions is a text classification model from ValenHumano. 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 16, 2023
- Updated
- Apr 16, 2023
- SHA
- 8ccb38b9
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Datasets
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. -->
bert-base-uncased-clasificator-emotions
This model is a fine-tuned version of bert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1825
- Accuracy: 0.9335
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1692 | 1.0 | 250 | 0.1858 | 0.931 |
| 0.1201 | 2.0 | 500 | 0.1818 | 0.9315 |
| 0.0829 | 3.0 | 750 | 0.1800 | 0.933 |
| 0.0568 | 4.0 | 1000 | 0.1825 | 0.9335 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Apr 16, 2023
- Updated
- Apr 16, 2023