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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- amazon_reviews_multi |
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widget: |
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- text: "me parece muy mal , se salía el producto por la caja y venían vacios , lo devolvere" |
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- text: "Correa de buena calidad, con un interior oscuro. Cumple perfectamente su función y se intercambia fácilmente. Una buena opción para cambiar el aspecto del reloj" |
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- text: "cumple su cometido sin nada que merezca la pena destacar" |
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metrics: |
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- accuracy |
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model-index: |
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- name: electricidad-small-finetuned-amazon-review-classification |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: amazon_reviews_multi |
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type: amazon_reviews_multi |
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args: es |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5832 |
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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-finetuned-amazon-review-classification |
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This model is a fine-tuned version of [mrm8488/electricidad-small-discriminator](https://huggingface.co/mrm8488/electricidad-small-discriminator) on the amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9506 |
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- Accuracy: 0.5832 |
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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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- 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.0258 | 1.0 | 6250 | 1.0209 | 0.5502 | |
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| 0.9668 | 2.0 | 12500 | 0.9960 | 0.565 | |
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| 0.953 | 3.0 | 18750 | 0.9802 | 0.5704 | |
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| 0.9201 | 4.0 | 25000 | 0.9831 | 0.567 | |
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| 0.902 | 5.0 | 31250 | 0.9814 | 0.5672 | |
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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 1.18.4 |
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- Tokenizers 0.11.6 |
