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hBERTv1_sst2
gokuls/hBERTv1_sst2
hBERTv1_sst2 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 1, 2023
- Updated
- Mar 2, 2023
- SHA
- 187f4126
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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_sst2
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4525
- Accuracy: 0.7901
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 |
|---|---|---|---|---|
| 0.6905 | 1.0 | 264 | 0.6919 | 0.5252 |
| 0.6609 | 2.0 | 528 | 0.6088 | 0.6915 |
| 0.4152 | 3.0 | 792 | 0.4525 | 0.7901 |
| 0.2611 | 4.0 | 1056 | 0.4627 | 0.8096 |
| 0.1953 | 5.0 | 1320 | 0.4894 | 0.8073 |
| 0.1588 | 6.0 | 1584 | 0.6002 | 0.8016 |
| 0.1336 | 7.0 | 1848 | 0.6467 | 0.8062 |
| 0.1117 | 8.0 | 2112 | 0.6409 | 0.8062 |
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 1, 2023
- Updated
- Mar 2, 2023