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SciBLOOM-ft-TweetAreas-ES
alecmontero/SciBLOOM-ft-TweetAreas-ES
SciBLOOM-ft-TweetAreas-ES is a text classification model from alecmontero. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as bigscience-bloom-rail-1.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- bigscience-bloom-rail-1.0
- Model type
- bloom
- Access
- Public
- Created
- Jul 25, 2024
- Updated
- Jul 25, 2024
- SHA
- af2e5c04
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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. -->
SciBLOOM-ft-TweetAreas-ES
This model is a fine-tuned version of bigscience/bloom-560m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4180
- Roc Auc: 0.8398
- Hamming Loss: 0.0450
- F1 Score: 0.7555
- Accuracy: 0.4712
- Precision: 0.8527
- Recall: 0.7085
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|---|---|
| 0.2275 | 1.0 | 747 | 0.3007 | 0.7245 | 0.0797 | 0.5268 | 0.2838 | 0.8290 | 0.4840 |
| 0.1338 | 2.0 | 1494 | 0.2027 | 0.7985 | 0.0611 | 0.6307 | 0.3788 | 0.7336 | 0.6296 |
| 0.1244 | 3.0 | 2241 | 0.1917 | 0.7985 | 0.0564 | 0.6552 | 0.4070 | 0.7901 | 0.6354 |
| 0.0459 | 4.0 | 2988 | 0.2264 | 0.8247 | 0.0535 | 0.7187 | 0.4110 | 0.8199 | 0.6832 |
| 0.046 | 5.0 | 3735 | 0.2932 | 0.8103 | 0.0541 | 0.6862 | 0.4003 | 0.8026 | 0.6552 |
| 0.0305 | 6.0 | 4482 | 0.3364 | 0.8318 | 0.0509 | 0.7236 | 0.4378 | 0.8015 | 0.7008 |
| 0.0075 | 7.0 | 5229 | 0.4112 | 0.8326 | 0.0482 | 0.7348 | 0.4418 | 0.8164 | 0.6929 |
| 0.001 | 8.0 | 5976 | 0.3984 | 0.8358 | 0.0466 | 0.7507 | 0.4538 | 0.8501 | 0.7022 |
| 0.0 | 9.0 | 6723 | 0.4134 | 0.8448 | 0.0454 | 0.7591 | 0.4712 | 0.8447 | 0.7198 |
| 0.0 | 10.0 | 7470 | 0.4180 | 0.8398 | 0.0450 | 0.7555 | 0.4712 | 0.8527 | 0.7085 |
Framework versions
- Transformers 4.43.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bloom
- License
- bigscience-bloom-rail-1.0
- Created
- Jul 25, 2024
- Updated
- Jul 25, 2024