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distilbert-base-uncased_emotion_ft_0517
land25/distilbert-base-uncased_emotion_ft_0517
distilbert-base-uncased_emotion_ft_0517 is a text classification model from land25. 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
- May 17, 2023
- Updated
- May 17, 2023
- SHA
- e022b9db
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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. -->
distilbert-base-uncased_emotion_ft_0517
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1479
- Accuracy: 0.9345
- F1: 0.9347
- Precision: 0.9088
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 | F1 | Precision |
|---|---|---|---|---|---|---|
| 0.7913 | 1.0 | 250 | 0.2689 | 0.918 | 0.9162 | 0.9016 |
| 0.2142 | 2.0 | 500 | 0.1764 | 0.929 | 0.9290 | 0.9109 |
| 0.1415 | 3.0 | 750 | 0.1541 | 0.934 | 0.9345 | 0.8995 |
| 0.1128 | 4.0 | 1000 | 0.1479 | 0.9345 | 0.9347 | 0.9088 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- May 17, 2023
- Updated
- May 17, 2023