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distilbert-base-uncased-finetuned-emo
Alexisbal/distilbert-base-uncased-finetuned-emo
distilbert-base-uncased-finetuned-emo is a text classification model from Alexisbal. 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
- distilbert
- Access
- Public
- Created
- Jun 10, 2023
- Updated
- Jun 19, 2023
- SHA
- 703918e6
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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. -->
distilbert-base-uncased-finetuned-emo
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3127
- Accuracy: 0.8775
- F1: 0.8775
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4049 | 1.0 | 500 | 0.3183 | 0.8655 | 0.8653 |
| 0.247 | 2.0 | 1000 | 0.3127 | 0.8775 | 0.8775 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.13.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jun 10, 2023
- Updated
- Jun 19, 2023