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bert-emotion
garrett-vangilder/bert-emotion
bert-emotion is a text classification model from garrett-vangilder. 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
- Nov 30, 2022
- Updated
- Dec 1, 2022
- SHA
- 227f7be1
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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-emotion
This model is a fine-tuned version of distilbert-base-cased on the tweet_eval dataset. It achieves the following results on the evaluation set:
- Loss: 1.1658
- Precision: 0.7311
- Recall: 0.7299
- Fscore: 0.7299
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
|---|---|---|---|---|---|---|
| 0.8562 | 1.0 | 815 | 0.7859 | 0.7527 | 0.6006 | 0.6173 |
| 0.5352 | 2.0 | 1630 | 0.9248 | 0.7545 | 0.7188 | 0.7293 |
| 0.2543 | 3.0 | 2445 | 1.1658 | 0.7311 | 0.7299 | 0.7299 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 30, 2022
- Updated
- Dec 1, 2022