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hBERTv1_no_pretrain_rte
gokuls/hBERTv1_no_pretrain_rte
hBERTv1_no_pretrain_rte 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
- Jun 15, 2023
- SHA
- 8b8047f8
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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_rte
This model is a fine-tuned version of on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6919
- Accuracy: 0.5271
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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7561 | 1.0 | 26 | 0.6977 | 0.4729 |
| 0.7108 | 2.0 | 52 | 0.7333 | 0.4729 |
| 0.7378 | 3.0 | 78 | 0.6919 | 0.5271 |
| 0.7045 | 4.0 | 104 | 0.7052 | 0.5271 |
| 0.7077 | 5.0 | 130 | 0.7034 | 0.5271 |
| 0.6816 | 6.0 | 156 | 0.7515 | 0.5343 |
| 0.6692 | 7.0 | 182 | 0.7616 | 0.5235 |
| 0.5846 | 8.0 | 208 | 0.9617 | 0.4838 |
Framework versions
- Transformers 4.30.2
- 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
- Jun 15, 2023