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distilbert-base-uncased-finetuned-emotion
satyaseeker333/distilbert-base-uncased-finetuned-emotion
distilbert-base-uncased-finetuned-emotion is a text classification model from satyaseeker333. 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
- Jun 10, 2023
- Updated
- Jun 10, 2023
- SHA
- b278516b
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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: 0.1382
- Accuracy: 0.941
- F1: 0.9411
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1911 | 1.0 | 125 | 0.1728 | 0.9285 | 0.9290 |
| 0.1302 | 2.0 | 250 | 0.1500 | 0.9365 | 0.9364 |
| 0.1068 | 3.0 | 375 | 0.1451 | 0.9365 | 0.9367 |
| 0.0912 | 4.0 | 500 | 0.1391 | 0.939 | 0.9389 |
| 0.077 | 5.0 | 625 | 0.1382 | 0.941 | 0.9411 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jun 10, 2023
- Updated
- Jun 10, 2023