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bert-base-uncased-finetuned-emotion
JayWang7/bert-base-uncased-finetuned-emotion
bert-base-uncased-finetuned-emotion is a text classification model from JayWang7. 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
- May 24, 2024
- Updated
- May 26, 2024
- SHA
- 2046940c
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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-finetuned-emotion
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: 0.2242
- Accuracy: 0.917
- F1: 0.9175
Model description
Label-0 = sadness Label-1 = joy Label-2 = love Label-3 = anger Label-4 = fear Label-5 = surprise
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 250 | 0.3240 | 0.8945 | 0.8928 |
| No log | 2.0 | 500 | 0.2242 | 0.917 | 0.9175 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 24, 2024
- Updated
- May 26, 2024