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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: miltilingual_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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# miltilingual_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: 1.1201 |
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- Accuracy: 0.6505 |
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- F1 Macro: 0.5674 |
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- Precision Macro: 0.5715 |
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- Recall Macro: 0.5690 |
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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: 1e-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: 8 |
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- total_train_batch_size: 64 |
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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: 10 |
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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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| 2.7395 | 1.0 | 1233 | 1.6602 | 0.5501 | 0.3447 | 0.3829 | 0.3645 | |
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| 1.5662 | 2.0 | 2466 | 1.2526 | 0.6228 | 0.5112 | 0.5447 | 0.5114 | |
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| 1.2526 | 3.0 | 3699 | 1.1599 | 0.6396 | 0.5478 | 0.5537 | 0.5551 | |
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| 1.1111 | 4.0 | 4932 | 1.1279 | 0.6469 | 0.5645 | 0.5619 | 0.5745 | |
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| 0.9426 | 5.0 | 6165 | 1.1201 | 0.6505 | 0.5674 | 0.5715 | 0.5690 | |
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| 0.8696 | 6.0 | 7398 | 1.1415 | 0.6462 | 0.5620 | 0.5645 | 0.5647 | |
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| 0.8271 | 7.0 | 8631 | 1.1486 | 0.6467 | 0.5657 | 0.5670 | 0.5667 | |
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| 0.7772 | 8.0 | 9864 | 1.1642 | 0.6477 | 0.5670 | 0.5644 | 0.5723 | |
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| 0.7247 | 9.0 | 11097 | 1.1731 | 0.6456 | 0.5644 | 0.5633 | 0.5676 | |
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| 0.7072 | 9.9922 | 12320 | 1.1731 | 0.6463 | 0.5658 | 0.5657 | 0.5677 | |
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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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