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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: albert-base-v2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: cf-albert-finetuned1 |
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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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# cf-albert-finetuned1 |
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4513 |
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- F1: 0.2897 |
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- Roc Auc: 0.5790 |
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- Accuracy: 0.0826 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.4712 | 1.0 | 908 | 0.4797 | 0.0104 | 0.5024 | 0.0055 | |
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| 0.4862 | 2.0 | 1816 | 0.4579 | 0.2726 | 0.5727 | 0.0936 | |
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| 0.4447 | 3.0 | 2724 | 0.4438 | 0.3161 | 0.5899 | 0.1101 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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