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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: spa-eng-pos-tagging-v2 |
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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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# spa-eng-pos-tagging-v2 |
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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: 0.4432 |
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- Accuracy: 0.8418 |
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- Precision: 0.8395 |
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- Recall: 0.7600 |
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- F1: 0.7676 |
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- Hamming Loss: 0.1582 |
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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: 12 |
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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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| 1.4285 | 1.0 | 1744 | 1.2584 | 0.5671 | 0.6506 | 0.4372 | 0.4716 | 0.4329 | |
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| 1.1788 | 2.0 | 3488 | 1.0023 | 0.6388 | 0.6753 | 0.5323 | 0.5578 | 0.3612 | |
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| 0.9144 | 3.0 | 5232 | 0.7885 | 0.7093 | 0.7259 | 0.6091 | 0.6281 | 0.2907 | |
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| 0.78 | 4.0 | 6976 | 0.6970 | 0.7439 | 0.7517 | 0.6527 | 0.6673 | 0.2561 | |
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| 0.6565 | 5.0 | 8720 | 0.6072 | 0.7765 | 0.7792 | 0.6838 | 0.6952 | 0.2235 | |
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| 0.5845 | 6.0 | 10464 | 0.5438 | 0.7995 | 0.7974 | 0.7125 | 0.7221 | 0.2005 | |
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| 0.5158 | 7.0 | 12208 | 0.5127 | 0.8132 | 0.8180 | 0.7250 | 0.7362 | 0.1868 | |
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| 0.4697 | 8.0 | 13952 | 0.4939 | 0.8186 | 0.8188 | 0.7345 | 0.7438 | 0.1814 | |
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| 0.4251 | 9.0 | 15696 | 0.4712 | 0.8334 | 0.8349 | 0.7502 | 0.7591 | 0.1666 | |
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| 0.4039 | 10.0 | 17440 | 0.4564 | 0.8381 | 0.8382 | 0.7538 | 0.7629 | 0.1619 | |
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| 0.3826 | 11.0 | 19184 | 0.4479 | 0.8397 | 0.8399 | 0.7565 | 0.7656 | 0.1603 | |
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| 0.3691 | 12.0 | 20928 | 0.4432 | 0.8418 | 0.8395 | 0.7600 | 0.7676 | 0.1582 | |
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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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