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hBERTv1_no_pretrain_cola
gokuls/hBERTv1_no_pretrain_cola
hBERTv1_no_pretrain_cola is a text classification model from gokuls. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- hybridbert
- Access
- Public
- Created
- May 29, 2023
- Updated
- May 29, 2023
- SHA
- 37833641
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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. -->
hBERTv1_no_pretrain_cola
This model is a fine-tuned version of on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6184
- Matthews Correlation: 0.0
- Accuracy: 0.6913
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: 0.0005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|---|---|---|---|---|---|
| 0.8952 | 1.0 | 67 | 0.6664 | 0.0 | 0.6913 |
| 0.6234 | 2.0 | 134 | 0.6184 | 0.0 | 0.6913 |
| 0.6127 | 3.0 | 201 | 0.6197 | 0.0 | 0.6913 |
| 0.6115 | 4.0 | 268 | 0.6209 | 0.0 | 0.6913 |
| 0.6096 | 5.0 | 335 | 0.6237 | 0.0 | 0.6913 |
| 0.6104 | 6.0 | 402 | 0.6209 | 0.0 | 0.6913 |
| 0.6123 | 7.0 | 469 | 0.6185 | 0.0 | 0.6913 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- hybridbert
- Languages
- en
- Created
- May 29, 2023
- Updated
- May 29, 2023