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--- |
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base_model: MMG/mlm-spanish-roberta-base |
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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: roberta-finetuned-gesture-prediction-es |
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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-finetuned-gesture-prediction-es |
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This model is a fine-tuned version of [MMG/mlm-spanish-roberta-base](https://huggingface.co/MMG/mlm-spanish-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7706 |
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- Accuracy: 0.7223 |
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- Precision: 0.7215 |
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- Recall: 0.7223 |
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- F1: 0.7156 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.8523 | 1.0 | 102 | 1.2237 | 0.6618 | 0.6205 | 0.6618 | 0.6316 | |
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| 1.0093 | 2.0 | 204 | 1.1357 | 0.6886 | 0.6715 | 0.6886 | 0.6663 | |
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| 0.6999 | 3.0 | 306 | 1.1758 | 0.6884 | 0.7008 | 0.6884 | 0.6763 | |
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| 0.4872 | 4.0 | 408 | 1.1398 | 0.6955 | 0.6982 | 0.6955 | 0.6839 | |
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| 0.3198 | 5.0 | 510 | 1.2017 | 0.7096 | 0.7112 | 0.7096 | 0.7059 | |
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| 0.2414 | 6.0 | 612 | 1.2819 | 0.7152 | 0.7101 | 0.7152 | 0.7049 | |
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| 0.1676 | 7.0 | 714 | 1.3279 | 0.7299 | 0.7272 | 0.7299 | 0.7221 | |
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| 0.1245 | 8.0 | 816 | 1.4593 | 0.7098 | 0.7078 | 0.7098 | 0.7011 | |
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| 0.0843 | 9.0 | 918 | 1.5682 | 0.7134 | 0.7131 | 0.7134 | 0.7063 | |
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| 0.0636 | 10.0 | 1020 | 1.5447 | 0.7195 | 0.7161 | 0.7195 | 0.7128 | |
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| 0.0464 | 11.0 | 1122 | 1.6686 | 0.7118 | 0.7164 | 0.7118 | 0.7050 | |
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| 0.0367 | 12.0 | 1224 | 1.6438 | 0.7251 | 0.7252 | 0.7251 | 0.7181 | |
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| 0.0292 | 13.0 | 1326 | 1.6803 | 0.7232 | 0.7199 | 0.7232 | 0.7170 | |
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| 0.0227 | 14.0 | 1428 | 1.6852 | 0.7217 | 0.7193 | 0.7217 | 0.7157 | |
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| 0.0155 | 15.0 | 1530 | 1.7753 | 0.7219 | 0.7245 | 0.7219 | 0.7156 | |
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| 0.0123 | 16.0 | 1632 | 1.7875 | 0.7157 | 0.7149 | 0.7157 | 0.7085 | |
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| 0.0102 | 17.0 | 1734 | 1.7649 | 0.7159 | 0.7148 | 0.7159 | 0.7095 | |
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| 0.0076 | 18.0 | 1836 | 1.7740 | 0.7204 | 0.7201 | 0.7204 | 0.7141 | |
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| 0.0074 | 19.0 | 1938 | 1.7674 | 0.7244 | 0.7235 | 0.7244 | 0.7177 | |
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| 0.0061 | 20.0 | 2040 | 1.7706 | 0.7223 | 0.7215 | 0.7223 | 0.7156 | |
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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 2.16.1 |
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- Tokenizers 0.15.0 |
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