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--- |
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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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- accuracy |
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- f1 |
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model-index: |
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- name: electricidad-base-ft-diagTrast |
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results: [] |
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widget: |
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- text: "Esta persona tiene una gran necesidad de atención y aprobación de los demás. Utiliza su aspecto físico para atraer la atención y muestra un comportamiento sexualmente seductor e inapropiado. Además, tiene dificultades para establecer relaciones auténticas y profundas con los demás" |
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- text: "Se comportaba de manera arrogante y altiva, como si estuviera por encima de todos los demás. Solía hablar en tono condescendiente y hacer sentir a los demás que eran inferiores a ella." |
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- text: "Siempre preocupada por quedarse sola, incluso en situaciones sociales, esta persona se esfuerza desesperadamente por evitar cualquier situación que la haga sentir desamparada, real o imaginada." |
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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 fine-tuned diagTrast |
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This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2111 |
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- Precision: 0.9653 |
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- Recall: 0.9627 |
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- Accuracy: 0.9627 |
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- F1: 0.9622 |
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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: 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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:| |
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| No log | 1.0 | 150 | 0.9281 | 0.7399 | 0.6567 | 0.6567 | 0.5989 | |
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| No log | 2.0 | 300 | 0.4736 | 0.8680 | 0.8582 | 0.8582 | 0.8581 | |
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| No log | 3.0 | 450 | 0.2584 | 0.9215 | 0.9104 | 0.9104 | 0.9110 | |
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| 0.6826 | 4.0 | 600 | 0.3336 | 0.9190 | 0.9104 | 0.9104 | 0.9036 | |
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| 0.6826 | 5.0 | 750 | 0.2194 | 0.9458 | 0.9403 | 0.9403 | 0.9398 | |
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| 0.6826 | 6.0 | 900 | 0.1984 | 0.9451 | 0.9403 | 0.9403 | 0.9397 | |
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| 0.0262 | 7.0 | 1050 | 0.2012 | 0.9582 | 0.9552 | 0.9552 | 0.9552 | |
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| 0.0262 | 8.0 | 1200 | 0.2272 | 0.9366 | 0.9328 | 0.9328 | 0.9319 | |
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| 0.0262 | 9.0 | 1350 | 0.2111 | 0.9653 | 0.9627 | 0.9627 | 0.9622 | |
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| 0.0044 | 10.0 | 1500 | 0.2156 | 0.9587 | 0.9552 | 0.9552 | 0.9543 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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