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finetuning-emotion-roberta
Suryakumar-P/finetuning-emotion-roberta
finetuning-emotion-roberta is a text classification model from Suryakumar-P. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Nov 11, 2024
- Updated
- Nov 12, 2024
- SHA
- 0c9743d3
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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. -->
finetuning-emotion-roberta
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3262
- Accuracy: 0.9365
- F1: 0.9366
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 250 | 0.2507 | 0.9145 | 0.9158 |
| 0.4547 | 2.0 | 500 | 0.1703 | 0.9305 | 0.9293 |
| 0.4547 | 3.0 | 750 | 0.1722 | 0.9335 | 0.9345 |
| 0.1329 | 4.0 | 1000 | 0.1377 | 0.939 | 0.9382 |
| 0.1329 | 5.0 | 1250 | 0.1443 | 0.941 | 0.9411 |
| 0.0979 | 6.0 | 1500 | 0.1355 | 0.936 | 0.9365 |
| 0.0979 | 7.0 | 1750 | 0.1581 | 0.94 | 0.9394 |
| 0.0788 | 8.0 | 2000 | 0.1680 | 0.9375 | 0.9378 |
| 0.0788 | 9.0 | 2250 | 0.1876 | 0.9345 | 0.9342 |
| 0.0593 | 10.0 | 2500 | 0.2207 | 0.9335 | 0.9342 |
| 0.0593 | 11.0 | 2750 | 0.2065 | 0.937 | 0.9375 |
| 0.0463 | 12.0 | 3000 | 0.2185 | 0.939 | 0.9390 |
| 0.0463 | 13.0 | 3250 | 0.2239 | 0.938 | 0.9380 |
| 0.0354 | 14.0 | 3500 | 0.2555 | 0.932 | 0.9320 |
| 0.0354 | 15.0 | 3750 | 0.3019 | 0.933 | 0.9330 |
| 0.0241 | 16.0 | 4000 | 0.3129 | 0.935 | 0.9351 |
| 0.0241 | 17.0 | 4250 | 0.3152 | 0.939 | 0.9387 |
| 0.0202 | 18.0 | 4500 | 0.3228 | 0.9345 | 0.9347 |
| 0.0202 | 19.0 | 4750 | 0.3224 | 0.937 | 0.9371 |
| 0.0148 | 20.0 | 5000 | 0.3262 | 0.9365 | 0.9366 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Nov 11, 2024
- Updated
- Nov 12, 2024