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bert_uncased_L-6_H-768_A-12-QAT
jysh1023/bert_uncased_L-6_H-768_A-12-QAT
bert_uncased_L-6_H-768_A-12-QAT is a text classification model from jysh1023. 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
- Nov 18, 2023
- Updated
- Nov 18, 2023
- SHA
- ae25767c
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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-6_H-768_A-12-QAT
This model is a fine-tuned version of google/bert_uncased_L-6_H-768_A-12 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.4989
- Accuracy: 0.8303
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: 6e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3055 | 1.0 | 8 | 0.4989 | 0.8303 |
| 0.192 | 2.0 | 16 | 0.4659 | 0.8108 |
| 0.0994 | 3.0 | 24 | 0.5389 | 0.8177 |
| 0.0324 | 4.0 | 32 | 0.7313 | 0.8096 |
| 0.0164 | 5.0 | 40 | 0.6689 | 0.8211 |
| 0.0137 | 6.0 | 48 | 0.7148 | 0.8154 |
| 0.0041 | 7.0 | 56 | 0.7339 | 0.8177 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 18, 2023
- Updated
- Nov 18, 2023