Trained model with classification head weights
Browse files
README.md
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---
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library_name: transformers
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base_model: allenai/scibert_scivocab_uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: defect-classification-scibert-baseline-10-epochs
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# defect-classification-scibert-baseline-10-epochs
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This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2972
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- Accuracy: 0.8919
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 256
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- eval_batch_size: 256
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.3931 | 1.0 | 2124 | 0.6939 | 0.8322 |
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| 0.9757 | 2.0 | 4248 | 0.4680 | 0.8614 |
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| 0.8006 | 3.0 | 6372 | 0.4260 | 0.8680 |
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| 0.712 | 4.0 | 8496 | 0.3813 | 0.8726 |
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| 0.6591 | 5.0 | 10620 | 0.3372 | 0.8840 |
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| 0.6215 | 6.0 | 12744 | 0.3446 | 0.8784 |
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| 0.5979 | 7.0 | 14868 | 0.3061 | 0.8922 |
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| 0.5791 | 8.0 | 16992 | 0.3035 | 0.8904 |
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| 0.5628 | 9.0 | 19116 | 0.2915 | 0.8947 |
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| 0.5662 | 10.0 | 21240 | 0.2972 | 0.8919 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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