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FNST_trad_h
mrovejaxd/FNST_trad_h
FNST_trad_h is a text classification model from mrovejaxd. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 24, 2024
- Updated
- May 24, 2024
- SHA
- ffced76c
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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. -->
FNST_trad_h
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3344
- Accuracy: 0.6633
- F1: 0.6496
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: 1e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 24
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.1493 | 1.0 | 1000 | 1.1016 | 0.5125 | 0.3623 |
| 0.9936 | 2.0 | 2000 | 0.9526 | 0.5942 | 0.5059 |
| 0.9056 | 3.0 | 3000 | 0.8908 | 0.6308 | 0.5971 |
| 0.8394 | 4.0 | 4000 | 0.8537 | 0.6425 | 0.6247 |
| 0.7877 | 5.0 | 5000 | 0.8308 | 0.6525 | 0.6362 |
| 0.7706 | 6.0 | 6000 | 0.8333 | 0.6608 | 0.6435 |
| 0.7142 | 7.0 | 7000 | 0.8258 | 0.6625 | 0.6505 |
| 0.6946 | 8.0 | 8000 | 0.8234 | 0.6617 | 0.6444 |
| 0.6525 | 9.0 | 9000 | 0.8367 | 0.6625 | 0.6518 |
| 0.6277 | 10.0 | 10000 | 0.8403 | 0.6583 | 0.6498 |
| 0.594 | 11.0 | 11000 | 0.8604 | 0.6583 | 0.6492 |
| 0.5691 | 12.0 | 12000 | 0.8701 | 0.665 | 0.6572 |
| 0.5268 | 13.0 | 13000 | 0.8956 | 0.6617 | 0.6534 |
| 0.5042 | 14.0 | 14000 | 0.9284 | 0.6583 | 0.6493 |
| 0.48 | 15.0 | 15000 | 0.9583 | 0.6567 | 0.6454 |
| 0.4507 | 16.0 | 16000 | 0.9734 | 0.6592 | 0.6479 |
| 0.4073 | 17.0 | 17000 | 1.0266 | 0.6617 | 0.6458 |
| 0.3838 | 18.0 | 18000 | 1.0626 | 0.6625 | 0.6477 |
| 0.3668 | 19.0 | 19000 | 1.0924 | 0.6575 | 0.6413 |
| 0.3439 | 20.0 | 20000 | 1.1276 | 0.6692 | 0.6595 |
| 0.3186 | 21.0 | 21000 | 1.1924 | 0.6608 | 0.6405 |
| 0.2926 | 22.0 | 22000 | 1.2392 | 0.6617 | 0.6468 |
| 0.2767 | 23.0 | 23000 | 1.2820 | 0.6658 | 0.6493 |
| 0.2531 | 24.0 | 24000 | 1.3344 | 0.6633 | 0.6496 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- May 24, 2024
- Updated
- May 24, 2024