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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-multilingual-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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: MBERT_uncased_SupervisedContrastiveCrossEntropyLoss_full_ft |
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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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# MBERT_uncased_SupervisedContrastiveCrossEntropyLoss_full_ft |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.714 |
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- F1: 0.8239 |
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- Precision: 0.7057 |
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- Recall: 0.9896 |
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- Roc Auc: 0.5643 |
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- Loss: 1.1941 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 | Precision | Recall | Roc Auc | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:------:|:---------:|:------:|:-------:|:---------------:| |
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| No log | 0.992 | 62 | 0.676 | 0.8067 | 0.676 | 1.0 | 0.5 | 1.2394 | |
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| 1.4051 | 2.0 | 125 | 0.676 | 0.8065 | 0.6764 | 0.9985 | 0.5008 | 1.1807 | |
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| 1.4051 | 2.976 | 186 | 0.714 | 0.8239 | 0.7057 | 0.9896 | 0.5643 | 1.1941 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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