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distilbert-base-uncased-finetuned-emotion
ocm/distilbert-base-uncased-finetuned-emotion
distilbert-base-uncased-finetuned-emotion is a text classification model from ocm. 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
- Oct 29, 2022
- Updated
- Nov 5, 2022
- SHA
- d16a5b85
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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-finetuned-emotion
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: 0.1582
- Accuracy: 0.935
- F1: 0.9351
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 |
|---|---|---|---|---|---|
| 0.7703 | 1.0 | 250 | 0.2588 | 0.918 | 0.9165 |
| 0.2031 | 2.0 | 500 | 0.1773 | 0.928 | 0.9282 |
| 0.1385 | 3.0 | 750 | 0.1593 | 0.934 | 0.9342 |
| 0.1101 | 4.0 | 1000 | 0.1582 | 0.935 | 0.9351 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 29, 2022
- Updated
- Nov 5, 2022