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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: google-bert/bert-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: bert-meme-classifier |
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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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# bert-meme-classifier |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0546 |
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- Accuracy: 0.46 |
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- Auc: 0.636 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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 | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:| |
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| 1.0854 | 1.0 | 560 | 1.0647 | 0.43 | 0.619 | |
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| 1.0549 | 2.0 | 1120 | 1.0566 | 0.453 | 0.62 | |
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| 1.0372 | 3.0 | 1680 | 1.0591 | 0.421 | 0.627 | |
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| 1.0232 | 4.0 | 2240 | 1.0514 | 0.46 | 0.633 | |
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| 1.0203 | 5.0 | 2800 | 1.0655 | 0.439 | 0.634 | |
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| 1.0237 | 6.0 | 3360 | 1.0529 | 0.469 | 0.636 | |
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| 1.006 | 7.0 | 3920 | 1.0576 | 0.442 | 0.635 | |
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| 1.0035 | 8.0 | 4480 | 1.0529 | 0.444 | 0.637 | |
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| 0.9947 | 9.0 | 5040 | 1.0544 | 0.447 | 0.635 | |
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| 0.9897 | 10.0 | 5600 | 1.0546 | 0.46 | 0.636 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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