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EmotiNet
Priyanshuchaudhary2425/EmotiNet
EmotiNet is a text classification model from Priyanshuchaudhary2425. 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
- Feb 25, 2024
- Updated
- Feb 25, 2024
- SHA
- a81b6873
Try a prompt
Base models
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. -->
EmotiNet
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3224
- Accuracy: 0.9242
- Precision: 0.8830
- Recall: 0.8990
- F1: 0.8902
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: 8
- eval_batch_size: 8
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1494 | 1.0 | 1500 | 0.3036 | 0.9237 | 0.8783 | 0.9166 | 0.8921 |
| 0.1481 | 2.0 | 3000 | 0.2944 | 0.9242 | 0.8893 | 0.8867 | 0.8877 |
| 0.072 | 3.0 | 4500 | 0.3224 | 0.9242 | 0.8830 | 0.8990 | 0.8902 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 25, 2024
- Updated
- Feb 25, 2024