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bert-base-uncased-sst2
gokuls/bert-base-uncased-sst2
bert-base-uncased-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. 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
- Jan 27, 2023
- Updated
- Jan 27, 2023
- SHA
- 853d9058
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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. -->
bert-base-uncased-sst2
This model is a fine-tuned version of bert-base-uncased on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2333
- Accuracy: 0.9128
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: 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2103 | 1.0 | 527 | 0.2507 | 0.9048 |
| 0.1082 | 2.0 | 1054 | 0.2333 | 0.9128 |
| 0.0724 | 3.0 | 1581 | 0.2371 | 0.9186 |
| 0.0521 | 4.0 | 2108 | 0.2582 | 0.9186 |
| 0.0393 | 5.0 | 2635 | 0.3094 | 0.9220 |
| 0.0302 | 6.0 | 3162 | 0.3506 | 0.9197 |
| 0.0258 | 7.0 | 3689 | 0.4149 | 0.9071 |
| 0.0209 | 8.0 | 4216 | 0.3121 | 0.9174 |
| 0.018 | 9.0 | 4743 | 0.4919 | 0.9060 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Languages
- en
- Created
- Jan 27, 2023
- Updated
- Jan 27, 2023