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test-trainer-glue-mrpc
P3ps/test-trainer-glue-mrpc
test-trainer-glue-mrpc is a text classification model from P3ps. 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
- May 8, 2023
- Updated
- May 8, 2023
- SHA
- 402b087d
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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. -->
test-trainer-glue-mrpc
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6850
- Accuracy: {'accuracy': 0.8627450980392157}
- F1: 0.9024
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.3762 | {'accuracy': 0.8455882352941176} | 0.8873 |
| 0.4903 | 2.0 | 918 | 0.5500 | {'accuracy': 0.8431372549019608} | 0.8923 |
| 0.2654 | 3.0 | 1377 | 0.6850 | {'accuracy': 0.8627450980392157} | 0.9024 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 8, 2023
- Updated
- May 8, 2023