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-20-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-20-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: 0.2422
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- Accuracy: 0.9124
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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: 20
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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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| 1.3805 | 1.0 | 2124 | 0.7077 | 0.8454 |
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| 0.9347 | 2.0 | 4248 | 0.4424 | 0.8740 |
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| 0.782 | 3.0 | 6372 | 0.3730 | 0.8907 |
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| 0.6677 | 4.0 | 8496 | 0.3447 | 0.8957 |
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| 0.6018 | 5.0 | 10620 | 0.3021 | 0.9057 |
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| 0.5746 | 6.0 | 12744 | 0.3155 | 0.8961 |
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| 0.5257 | 7.0 | 14868 | 0.2747 | 0.9100 |
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| 0.5162 | 8.0 | 16992 | 0.2639 | 0.9104 |
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| 0.4955 | 9.0 | 19116 | 0.2921 | 0.8975 |
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| 0.4763 | 10.0 | 21240 | 0.2684 | 0.9036 |
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| 0.4579 | 11.0 | 23364 | 0.2657 | 0.9069 |
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| 0.454 | 12.0 | 25488 | 0.2535 | 0.9114 |
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| 0.4384 | 13.0 | 27612 | 0.2626 | 0.9039 |
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| 0.428 | 14.0 | 29736 | 0.2620 | 0.9011 |
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| 0.4262 | 15.0 | 31860 | 0.2411 | 0.9141 |
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| 0.425 | 16.0 | 33984 | 0.2586 | 0.9035 |
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| 0.4141 | 17.0 | 36108 | 0.2446 | 0.9117 |
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| 0.4129 | 18.0 | 38232 | 0.2506 | 0.9073 |
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| 0.4105 | 19.0 | 40356 | 0.2424 | 0.9132 |
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| 0.4099 | 20.0 | 42480 | 0.2422 | 0.9124 |
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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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