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--- |
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license: apache-2.0 |
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base_model: 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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/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: 0.4465 |
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- Accuracy: 0.8226 |
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- F1: 0.8220 |
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- Precision: 0.8231 |
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- Recall: 0.8226 |
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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: 4.993596574084884e-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: 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 | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.0218 | 1.0 | 622 | 0.8816 | 0.5732 | 0.5732 | 0.5812 | 0.5732 | |
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| 0.8654 | 2.0 | 1244 | 0.7610 | 0.6600 | 0.6539 | 0.6620 | 0.6600 | |
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| 0.7534 | 3.0 | 1866 | 0.6904 | 0.6962 | 0.6912 | 0.7079 | 0.6962 | |
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| 0.6593 | 4.0 | 2488 | 0.6406 | 0.7342 | 0.7290 | 0.7454 | 0.7342 | |
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| 0.5278 | 5.0 | 3110 | 0.5557 | 0.7740 | 0.7732 | 0.7763 | 0.7740 | |
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| 0.4939 | 6.0 | 3732 | 0.5420 | 0.7776 | 0.7764 | 0.7819 | 0.7776 | |
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| 0.4585 | 7.0 | 4354 | 0.5258 | 0.7920 | 0.7899 | 0.7999 | 0.7920 | |
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| 0.4181 | 8.0 | 4976 | 0.5013 | 0.8029 | 0.8023 | 0.8046 | 0.8029 | |
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| 0.3804 | 9.0 | 5598 | 0.4922 | 0.8065 | 0.8053 | 0.8109 | 0.8065 | |
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| 0.3642 | 10.0 | 6220 | 0.4823 | 0.8065 | 0.8056 | 0.8085 | 0.8065 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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