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--- |
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language: es |
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license: afl-3.0 |
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tags: |
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- generated_from_trainer |
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- sentiment |
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- emotion |
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metrics: |
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- accuracy |
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widget: |
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- text: La vida no merece la pena |
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example_title: Ejemplo 1 |
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- text: Para vivir así lo mejor es estar muerto |
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example_title: Ejemplo 2 |
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- text: me siento triste por no poder viajar |
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example_title: Ejemplo 3 |
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- text: Quiero terminar con todo |
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example_title: Ejemplo 4 |
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- text: Disfruto de la vista |
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example_title: Ejemplo 5 |
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base_model: mrm8488/electricidad-small-discriminator |
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model-index: |
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- name: electricidad-small-discriminator-finetuned-clasificacion-texto-suicida |
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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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# electricidad-small-discriminator-finetuned-clasificacion-texto-suicida |
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This model is a fine-tuned version of [mrm8488/electricidad-small-discriminator](https://huggingface.co/mrm8488/electricidad-small-discriminator) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0458 |
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- Accuracy: 0.9916 |
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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: 32 |
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- eval_batch_size: 32 |
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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 | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:---------------:|:--------:| |
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| 0.161100 | 1.0 | 0.133057 | 0.952718 | |
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| 0.134500 | 2.0 | 0.110966 | 0.960804 | |
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| 0.108500 | 3.0 | 0.086417 | 0.970835 | |
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| 0.099400 | 4.0 | 0.073618 | 0.974856 | |
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| 0.090500 | 5.0 | 0.065231 | 0.979629 | |
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| 0.080700 | 6.0 | 0.060849 | 0.982324 | |
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| 0.069200 | 7.0 | 0.054718 | 0.986125 | |
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| 0.060400 | 8.0 | 0.051153 | 0.985948 | |
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| 0.048200 | 9.0 | 0.045747 | 0.989748 | |
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| 0.045500 | 10.0 | 0.049992 | 0.988069 | |
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| 0.043400 | 11.0 | 0.046325 | 0.990234 | |
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| 0.034300 | 12.0 | 0.050746 | 0.989792 | |
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| 0.032900 | 13.0 | 0.043434 | 0.991737 | |
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| 0.028400 | 14.0 | 0.045003 | 0.991869 | |
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| 0.022300 | 15.0 | 0.045819 | 0.991648 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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