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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-multilingual-cased |
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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: multilingual_dbert_linsearch_only_abstract |
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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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# multilingual_dbert_linsearch_only_abstract |
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5452 |
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- Accuracy: 0.6465 |
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- F1 Macro: 0.5744 |
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- Precision Macro: 0.5998 |
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- Recall Macro: 0.5660 |
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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: 4 |
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- eval_batch_size: 4 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:| |
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| 1.3208 | 1.0 | 19722 | 1.2841 | 0.6142 | 0.5160 | 0.5368 | 0.5359 | |
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| 1.1135 | 2.0 | 39444 | 1.1921 | 0.6449 | 0.5597 | 0.5673 | 0.5575 | |
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| 0.8989 | 3.0 | 59166 | 1.2967 | 0.6495 | 0.5643 | 0.5834 | 0.5573 | |
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| 0.7155 | 4.0 | 78888 | 1.5452 | 0.6465 | 0.5744 | 0.5998 | 0.5660 | |
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| 0.5373 | 5.0 | 98610 | 1.7780 | 0.6400 | 0.5669 | 0.5895 | 0.5605 | |
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### Framework versions |
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- Transformers 4.50.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
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