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bert_uncased_L-4_H-256_A-4_stsb
gokulsrinivasagan/bert_uncased_L-4_H-256_A-4_stsb
bert_uncased_L-4_H-256_A-4_stsb is a text classification model from gokulsrinivasagan. 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
- Dec 4, 2024
- Updated
- Dec 4, 2024
- SHA
- ff529ab3
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Base models
Datasets
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. -->
bert_uncased_L-4_H-256_A-4_stsb
This model is a fine-tuned version of google/bert_uncased_L-4_H-256_A-4 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 0.6283
- Pearson: 0.8545
- Spearmanr: 0.8542
- Combined Score: 0.8543
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 5.5773 | 1.0 | 23 | 2.7412 | 0.3845 | 0.3343 | 0.3594 |
| 2.5793 | 2.0 | 46 | 1.9158 | 0.7727 | 0.7557 | 0.7642 |
| 1.5767 | 3.0 | 69 | 0.9541 | 0.7706 | 0.7473 | 0.7590 |
| 0.9474 | 4.0 | 92 | 0.7628 | 0.8133 | 0.8070 | 0.8101 |
| 0.7258 | 5.0 | 115 | 0.6785 | 0.8383 | 0.8429 | 0.8406 |
| 0.6162 | 6.0 | 138 | 0.6756 | 0.8436 | 0.8439 | 0.8437 |
| 0.5455 | 7.0 | 161 | 0.6391 | 0.8480 | 0.8504 | 0.8492 |
| 0.4912 | 8.0 | 184 | 0.6582 | 0.8461 | 0.8472 | 0.8466 |
| 0.4443 | 9.0 | 207 | 0.6561 | 0.8472 | 0.8482 | 0.8477 |
| 0.3995 | 10.0 | 230 | 0.6429 | 0.8504 | 0.8503 | 0.8503 |
| 0.3689 | 11.0 | 253 | 0.6283 | 0.8545 | 0.8542 | 0.8543 |
| 0.3418 | 12.0 | 276 | 0.6592 | 0.8520 | 0.8520 | 0.8520 |
| 0.3302 | 13.0 | 299 | 0.6507 | 0.8524 | 0.8530 | 0.8527 |
| 0.319 | 14.0 | 322 | 0.6484 | 0.8528 | 0.8526 | 0.8527 |
| 0.2863 | 15.0 | 345 | 0.6397 | 0.8526 | 0.8527 | 0.8526 |
| 0.2774 | 16.0 | 368 | 0.6379 | 0.8559 | 0.8555 | 0.8557 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Languages
- en
- Created
- Dec 4, 2024
- Updated
- Dec 4, 2024