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bert-emotion
tamarab/bert-emotion
bert-emotion is a text classification model from tamarab. 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 20, 2022
- Updated
- May 20, 2022
- SHA
- 22be9f5e
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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: 1.1347
- Precision: 0.7463
- Recall: 0.7096
- Fscore: 0.7209
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 |
|---|---|---|---|---|---|---|
| 0.8385 | 1.0 | 815 | 0.8366 | 0.7865 | 0.5968 | 0.6014 |
| 0.5451 | 2.0 | 1630 | 0.9301 | 0.7301 | 0.6826 | 0.6947 |
| 0.2447 | 3.0 | 2445 | 1.1347 | 0.7463 | 0.7096 | 0.7209 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- May 20, 2022
- Updated
- May 20, 2022