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bert_finetuned_shortstories
sert121/bert_finetuned_shortstories
bert_finetuned_shortstories is a text classification model from sert121. 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
- Jun 27, 2023
- Updated
- Feb 7, 2024
- SHA
- 503c3286
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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. -->
results
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4272
- Accuracy: 0.8218
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: 16
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6987 | 0.53 | 10 | 0.7055 | 0.4158 |
| 0.6893 | 1.05 | 20 | 0.6336 | 0.7327 |
| 0.5912 | 1.58 | 30 | 0.6067 | 0.7129 |
| 0.4819 | 2.11 | 40 | 0.4757 | 0.7822 |
| 0.2509 | 2.63 | 50 | 0.4272 | 0.8218 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jun 27, 2023
- Updated
- Feb 7, 2024