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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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- precision |
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- recall |
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- f1 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5702 |
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- Accuracy: 0.7894 |
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- Precision: 0.7913 |
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- Recall: 0.7040 |
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- F1: 0.7144 |
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- Hamming Loss: 0.2106 |
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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: 16 |
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- eval_batch_size: 32 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming Loss | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:| |
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| 1.435 | 1.0 | 1744 | 1.2662 | 0.5627 | 0.6403 | 0.4392 | 0.4707 | 0.4373 | |
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| 1.19 | 2.0 | 3488 | 1.0175 | 0.6358 | 0.6749 | 0.5311 | 0.5571 | 0.3642 | |
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| 0.9496 | 3.0 | 5232 | 0.8298 | 0.6934 | 0.7166 | 0.5916 | 0.6132 | 0.3066 | |
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| 0.8226 | 4.0 | 6976 | 0.7224 | 0.7306 | 0.7447 | 0.6371 | 0.6561 | 0.2694 | |
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| 0.7113 | 5.0 | 8720 | 0.6609 | 0.7514 | 0.7628 | 0.6583 | 0.6742 | 0.2486 | |
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| 0.6497 | 6.0 | 10464 | 0.6153 | 0.7724 | 0.7717 | 0.6904 | 0.6980 | 0.2276 | |
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| 0.5997 | 7.0 | 12208 | 0.5822 | 0.7863 | 0.7945 | 0.6967 | 0.7105 | 0.2137 | |
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| 0.571 | 8.0 | 13952 | 0.5702 | 0.7894 | 0.7913 | 0.7040 | 0.7144 | 0.2106 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.0.1+cu118 |
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- Tokenizers 0.13.3 |
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