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scenario-TCR-data-glue-mrpc-model-bert-base-uncased
haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased
scenario-TCR-data-glue-mrpc-model-bert-base-uncased is a text classification model from haryoaw. 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 29, 2023
- Updated
- Jan 10, 2024
- SHA
- 7599d2d9
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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. -->
scenario-TCR-data-glue-mrpc-model-bert-base-uncased
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8418
- Accuracy: 0.8431
- F1: 0.8869
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6969
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 115 | 0.3798 | 0.8578 | 0.8945 |
| No log | 2.0 | 230 | 0.4539 | 0.8113 | 0.8752 |
| No log | 3.0 | 345 | 0.4868 | 0.8309 | 0.8852 |
| No log | 4.0 | 460 | 0.7806 | 0.8333 | 0.8745 |
| 0.2296 | 5.0 | 575 | 0.6896 | 0.8627 | 0.9028 |
| 0.2296 | 6.0 | 690 | 1.1197 | 0.8235 | 0.8788 |
| 0.2296 | 7.0 | 805 | 0.9408 | 0.8456 | 0.8930 |
| 0.2296 | 8.0 | 920 | 0.9377 | 0.8284 | 0.8805 |
| 0.0295 | 9.0 | 1035 | 1.0580 | 0.8137 | 0.8770 |
| 0.0295 | 10.0 | 1150 | 0.8418 | 0.8431 | 0.8869 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 29, 2023
- Updated
- Jan 10, 2024