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--- |
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license: apache-2.0 |
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base_model: PlanTL-GOB-ES/roberta-base-bne |
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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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- f1 |
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- accuracy |
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model-index: |
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- name: roberta-base-bne-ner |
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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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# roberta-base-bne-ner |
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This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3159 |
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- Precision: 0.8517 |
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- Recall: 0.8933 |
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- F1: 0.8720 |
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- Accuracy: 0.9384 |
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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: 2e-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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 280 | 0.3006 | 0.7961 | 0.8563 | 0.8251 | 0.9164 | |
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| 0.4008 | 2.0 | 560 | 0.2984 | 0.7918 | 0.8622 | 0.8255 | 0.9203 | |
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| 0.4008 | 3.0 | 840 | 0.2324 | 0.8401 | 0.8563 | 0.8481 | 0.9343 | |
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| 0.1014 | 4.0 | 1120 | 0.2394 | 0.8242 | 0.8889 | 0.8553 | 0.9414 | |
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| 0.1014 | 5.0 | 1400 | 0.2674 | 0.8469 | 0.8933 | 0.8695 | 0.9371 | |
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| 0.0435 | 6.0 | 1680 | 0.2815 | 0.8255 | 0.8830 | 0.8533 | 0.9375 | |
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| 0.0435 | 7.0 | 1960 | 0.2713 | 0.8516 | 0.8844 | 0.8677 | 0.9444 | |
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| 0.0233 | 8.0 | 2240 | 0.2745 | 0.8541 | 0.8933 | 0.8733 | 0.9437 | |
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| 0.0177 | 9.0 | 2520 | 0.3383 | 0.8336 | 0.8978 | 0.8645 | 0.9350 | |
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| 0.0177 | 10.0 | 2800 | 0.2858 | 0.8606 | 0.8963 | 0.8781 | 0.9419 | |
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| 0.013 | 11.0 | 3080 | 0.2956 | 0.8350 | 0.8919 | 0.8625 | 0.9403 | |
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| 0.013 | 12.0 | 3360 | 0.3097 | 0.8423 | 0.9022 | 0.8712 | 0.9380 | |
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| 0.0104 | 13.0 | 3640 | 0.3158 | 0.8443 | 0.8919 | 0.8674 | 0.9380 | |
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| 0.0104 | 14.0 | 3920 | 0.3171 | 0.8493 | 0.8933 | 0.8708 | 0.9387 | |
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| 0.0088 | 15.0 | 4200 | 0.3159 | 0.8517 | 0.8933 | 0.8720 | 0.9384 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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