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sa_BERT_no_pretrain_qnli
gokuls/sa_BERT_no_pretrain_qnli
sa_BERT_no_pretrain_qnli 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. 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
- May 29, 2023
- Updated
- Jun 14, 2023
- SHA
- 8f8df125
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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. -->
sa_BERT_no_pretrain_qnli
This model is a fine-tuned version of bert-base-uncased on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6547
- Accuracy: 0.6059
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 |
|---|---|---|---|---|
| 0.6847 | 1.0 | 1092 | 0.6580 | 0.6068 |
| 0.6491 | 2.0 | 2184 | 0.6547 | 0.6059 |
| 0.6223 | 3.0 | 3276 | 0.6778 | 0.6021 |
| 0.5814 | 4.0 | 4368 | 0.7237 | 0.5843 |
| 0.5176 | 5.0 | 5460 | 0.7387 | 0.5757 |
| 0.4447 | 6.0 | 6552 | 0.8224 | 0.5733 |
| 0.3761 | 7.0 | 7644 | 0.9915 | 0.5598 |
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
- bert
- License
- apache-2.0
- Languages
- en
- Created
- May 29, 2023
- Updated
- Jun 14, 2023