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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license: apache-2.0
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base_model: distilbert/distilbert-base-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-distilbert-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-distilbert-baseline-10-epochs
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2976
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- Accuracy: 0.8762
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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: 512
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- eval_batch_size: 512
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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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| 0.6008 | 1.0 | 1062 | 0.5867 | 0.7578 |
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| 0.4986 | 2.0 | 2124 | 0.4298 | 0.8051 |
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| 0.4322 | 3.0 | 3186 | 0.3786 | 0.8255 |
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| 0.458 | 4.0 | 4248 | 0.3425 | 0.8462 |
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| 0.4143 | 5.0 | 5310 | 0.3274 | 0.8533 |
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| 0.4443 | 6.0 | 6372 | 0.3153 | 0.8620 |
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| 0.3508 | 7.0 | 7434 | 0.3076 | 0.8691 |
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| 0.4489 | 8.0 | 8496 | 0.2989 | 0.8745 |
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| 0.364 | 9.0 | 9558 | 0.2974 | 0.8764 |
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| 0.4091 | 10.0 | 10620 | 0.2976 | 0.8762 |
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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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