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SciGPT2-ft-TweetAreas-ES
alecmontero/SciGPT2-ft-TweetAreas-ES
SciGPT2-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 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
- gpt2
- Access
- Public
- Created
- Jul 24, 2024
- Updated
- Jul 24, 2024
- SHA
- b75127d8
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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. -->
SciGPT2-ft-TweetAreas-ES
This model is a fine-tuned version of DeepESP/gpt2-spanish on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2090
- Roc Auc: 0.7863
- Hamming Loss: 0.0548
- F1 Score: 0.6523
- Accuracy: 0.4083
- Precision: 0.8301
- Recall: 0.6023
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|---|---|
| 0.1499 | 1.0 | 747 | 0.1910 | 0.7062 | 0.0689 | 0.4861 | 0.3320 | 0.8506 | 0.4443 |
| 0.1593 | 2.0 | 1494 | 0.1707 | 0.7546 | 0.0636 | 0.5862 | 0.3494 | 0.7958 | 0.5444 |
| 0.1042 | 3.0 | 2241 | 0.1700 | 0.7718 | 0.0617 | 0.6133 | 0.3748 | 0.7891 | 0.5812 |
| 0.0455 | 4.0 | 2988 | 0.1786 | 0.7934 | 0.0585 | 0.6533 | 0.3855 | 0.7900 | 0.6232 |
| 0.0378 | 5.0 | 3735 | 0.1896 | 0.7903 | 0.0571 | 0.6564 | 0.3882 | 0.8020 | 0.6093 |
| 0.0199 | 6.0 | 4482 | 0.1948 | 0.7983 | 0.0566 | 0.6627 | 0.3949 | 0.7763 | 0.6304 |
| 0.0101 | 7.0 | 5229 | 0.2014 | 0.7888 | 0.0553 | 0.6625 | 0.3963 | 0.8127 | 0.6069 |
| 0.0087 | 8.0 | 5976 | 0.2059 | 0.7830 | 0.0563 | 0.6507 | 0.3922 | 0.8271 | 0.5969 |
| 0.0071 | 9.0 | 6723 | 0.2074 | 0.7888 | 0.0550 | 0.6587 | 0.4070 | 0.8304 | 0.6080 |
| 0.0047 | 10.0 | 7470 | 0.2090 | 0.7863 | 0.0548 | 0.6523 | 0.4083 | 0.8301 | 0.6023 |
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
- gpt2
- License
- mit
- Created
- Jul 24, 2024
- Updated
- Jul 24, 2024