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defect-classification-scibert-baseline-05-epochs
ppak10/defect-classification-scibert-baseline-05-epochs
defect-classification-scibert-baseline-05-epochs is a machine learning model from ppak10. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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Updated Jan 18, 2025
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At a glance
- Library
- transformers
- Access
- Public
- Created
- Jan 17, 2025
- Updated
- Jan 18, 2025
- SHA
- 1a5b0dd0
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. -->
defect-classification-scibert-baseline-05-epochs
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4110
- Accuracy: 0.8821
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: 2e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3603 | 1.0 | 2124 | 0.7726 | 0.8380 |
| 0.9928 | 2.0 | 4248 | 0.5648 | 0.8593 |
| 0.8523 | 3.0 | 6372 | 0.5076 | 0.8665 |
| 0.7912 | 4.0 | 8496 | 0.4389 | 0.8767 |
| 0.7593 | 5.0 | 10620 | 0.4110 | 0.8821 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Library
- transformers
- Created
- Jan 17, 2025
- Updated
- Jan 18, 2025