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roberta-base-sst-2-16-13-30
simonycl/roberta-base-sst-2-16-13-30
roberta-base-sst-2-16-13-30 is a text classification model from simonycl. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Aug 9, 2023
- Updated
- Aug 9, 2023
- SHA
- 3a21b689
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Base models
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. -->
roberta-base-sst-2-16-13-30
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6585
- Accuracy: 0.6875
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 0.6934 | 0.5 |
| No log | 2.0 | 2 | 0.6933 | 0.5 |
| No log | 3.0 | 3 | 0.6933 | 0.5 |
| No log | 4.0 | 4 | 0.6929 | 0.5 |
| No log | 5.0 | 5 | 0.6925 | 0.5 |
| No log | 6.0 | 6 | 0.6920 | 0.5 |
| No log | 7.0 | 7 | 0.6914 | 0.5 |
| No log | 8.0 | 8 | 0.6909 | 0.6875 |
| No log | 9.0 | 9 | 0.6904 | 0.625 |
| 0.6897 | 10.0 | 10 | 0.6899 | 0.5 |
| 0.6897 | 11.0 | 11 | 0.6894 | 0.5 |
| 0.6897 | 12.0 | 12 | 0.6888 | 0.5 |
| 0.6897 | 13.0 | 13 | 0.6880 | 0.5312 |
| 0.6897 | 14.0 | 14 | 0.6871 | 0.5312 |
| 0.6897 | 15.0 | 15 | 0.6860 | 0.5312 |
| 0.6897 | 16.0 | 16 | 0.6849 | 0.6562 |
| 0.6897 | 17.0 | 17 | 0.6836 | 0.7188 |
| 0.6897 | 18.0 | 18 | 0.6821 | 0.6875 |
| 0.6897 | 19.0 | 19 | 0.6805 | 0.6875 |
| 0.6642 | 20.0 | 20 | 0.6788 | 0.6875 |
| 0.6642 | 21.0 | 21 | 0.6768 | 0.7188 |
| 0.6642 | 22.0 | 22 | 0.6746 | 0.7188 |
| 0.6642 | 23.0 | 23 | 0.6723 | 0.7188 |
| 0.6642 | 24.0 | 24 | 0.6696 | 0.7188 |
| 0.6642 | 25.0 | 25 | 0.6670 | 0.6875 |
| 0.6642 | 26.0 | 26 | 0.6644 | 0.6875 |
| 0.6642 | 27.0 | 27 | 0.6622 | 0.7188 |
| 0.6642 | 28.0 | 28 | 0.6604 | 0.7188 |
| 0.6642 | 29.0 | 29 | 0.6592 | 0.6875 |
| 0.5945 | 30.0 | 30 | 0.6585 | 0.6875 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Aug 9, 2023
- Updated
- Aug 9, 2023