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--- |
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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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- precision |
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- recall |
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model-index: |
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- name: distilbert-base-multilingual-cased-lora-text-classification |
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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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# distilbert-base-multilingual-cased-lora-text-classification |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5474 |
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- Precision: 0.7635 |
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- Recall: 0.9338 |
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- F1 and accuracy: {'accuracy': 0.7456359102244389, 'f1': 0.8401253918495297} |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 and accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:----------------------------------------------------------:| |
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| No log | 1.0 | 401 | 0.6017 | 0.7157 | 1.0 | {'accuracy': 0.71571072319202, 'f1': 0.8343023255813953} | |
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| 0.5798 | 2.0 | 802 | 0.5967 | 0.7157 | 1.0 | {'accuracy': 0.71571072319202, 'f1': 0.8343023255813953} | |
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| 0.5546 | 3.0 | 1203 | 0.5722 | 0.7157 | 1.0 | {'accuracy': 0.71571072319202, 'f1': 0.8343023255813953} | |
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| 0.5403 | 4.0 | 1604 | 0.5624 | 0.7259 | 0.9965 | {'accuracy': 0.7281795511221946, 'f1': 0.8399412628487517} | |
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| 0.5206 | 5.0 | 2005 | 0.5597 | 0.7368 | 0.9756 | {'accuracy': 0.7331670822942643, 'f1': 0.8395802098950524} | |
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| 0.5206 | 6.0 | 2406 | 0.5588 | 0.7520 | 0.9617 | {'accuracy': 0.7456359102244389, 'f1': 0.8440366972477064} | |
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| 0.5153 | 7.0 | 2807 | 0.5679 | 0.7554 | 0.9686 | {'accuracy': 0.7531172069825436, 'f1': 0.8488549618320611} | |
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| 0.4959 | 8.0 | 3208 | 0.5693 | 0.7576 | 0.9582 | {'accuracy': 0.7506234413965087, 'f1': 0.8461538461538461} | |
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| 0.4801 | 9.0 | 3609 | 0.5466 | 0.7635 | 0.9338 | {'accuracy': 0.7456359102244389, 'f1': 0.8401253918495297} | |
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| 0.4949 | 10.0 | 4010 | 0.5474 | 0.7635 | 0.9338 | {'accuracy': 0.7456359102244389, 'f1': 0.8401253918495297} | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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