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bert_uncased_L-2_H-128_A-2_mrpc
gokulsrinivasagan/bert_uncased_L-2_H-128_A-2_mrpc
bert_uncased_L-2_H-128_A-2_mrpc 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
- 22f8f1f2
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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-2_H-128_A-2_mrpc
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5352
- Accuracy: 0.7328
- F1: 0.8233
- Combined Score: 0.7781
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 | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6493 | 1.0 | 15 | 0.6227 | 0.6838 | 0.8122 | 0.7480 |
| 0.6257 | 2.0 | 30 | 0.6134 | 0.6838 | 0.8122 | 0.7480 |
| 0.6126 | 3.0 | 45 | 0.6052 | 0.6838 | 0.8122 | 0.7480 |
| 0.6036 | 4.0 | 60 | 0.5954 | 0.6961 | 0.8176 | 0.7569 |
| 0.5897 | 5.0 | 75 | 0.5879 | 0.6985 | 0.8167 | 0.7576 |
| 0.5781 | 6.0 | 90 | 0.5741 | 0.7034 | 0.8158 | 0.7596 |
| 0.5635 | 7.0 | 105 | 0.5711 | 0.7108 | 0.8201 | 0.7655 |
| 0.5429 | 8.0 | 120 | 0.5674 | 0.7132 | 0.8208 | 0.7670 |
| 0.5228 | 9.0 | 135 | 0.5685 | 0.7206 | 0.8252 | 0.7729 |
| 0.5057 | 10.0 | 150 | 0.5497 | 0.7304 | 0.8281 | 0.7793 |
| 0.4856 | 11.0 | 165 | 0.5438 | 0.7377 | 0.8293 | 0.7835 |
| 0.4657 | 12.0 | 180 | 0.5352 | 0.7328 | 0.8233 | 0.7781 |
| 0.4447 | 13.0 | 195 | 0.5435 | 0.7402 | 0.8323 | 0.7862 |
| 0.4175 | 14.0 | 210 | 0.5562 | 0.7402 | 0.8328 | 0.7865 |
| 0.4039 | 15.0 | 225 | 0.5759 | 0.7426 | 0.8357 | 0.7892 |
| 0.3964 | 16.0 | 240 | 0.5610 | 0.7377 | 0.8299 | 0.7838 |
| 0.3735 | 17.0 | 255 | 0.5587 | 0.7377 | 0.8283 | 0.7830 |
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