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hBERTv2_data_aug_rte
gokuls/hBERTv2_data_aug_rte
hBERTv2_data_aug_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
- Mar 5, 2023
- Updated
- Mar 5, 2023
- SHA
- 123e3dd5
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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. -->
hBERTv2_data_aug_rte
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2 on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 1.3232
- Accuracy: 0.4910
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: 256
- eval_batch_size: 256
- 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 | Accuracy |
|---|---|---|---|---|
| 0.6262 | 1.0 | 568 | 1.3232 | 0.4910 |
| 0.0855 | 2.0 | 1136 | 2.3457 | 0.4946 |
| 0.022 | 3.0 | 1704 | 2.9797 | 0.5018 |
| 0.0128 | 4.0 | 2272 | 2.6395 | 0.5271 |
| 0.0085 | 5.0 | 2840 | 3.1634 | 0.5379 |
| 0.0059 | 6.0 | 3408 | 3.5948 | 0.5199 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- hybridbert
- Languages
- en
- Created
- Mar 5, 2023
- Updated
- Mar 5, 2023