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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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- dataset |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: dccuchile-distilbert-base-spanish-uncased-finetuned-with-spanish-tweets-clf |
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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: dataset |
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type: dataset |
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config: 60-20-20 |
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split: dev |
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args: 60-20-20 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6620594333102972 |
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- name: F1 |
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type: f1 |
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value: 0.6612467747613665 |
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- name: Precision |
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type: precision |
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value: 0.6698857111668722 |
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- name: Recall |
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type: recall |
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value: 0.6593066578581652 |
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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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# dccuchile-distilbert-base-spanish-uncased-finetuned-with-spanish-tweets-clf |
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This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on the dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5271 |
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- Accuracy: 0.6621 |
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- F1: 0.6612 |
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- Precision: 0.6699 |
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- Recall: 0.6593 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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: 4.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.8515 | 1.0 | 543 | 0.7681 | 0.6565 | 0.6374 | 0.6491 | 0.6363 | |
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| 0.5505 | 2.0 | 1086 | 0.8494 | 0.6489 | 0.6431 | 0.6713 | 0.6357 | |
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| 0.3302 | 3.0 | 1629 | 1.2386 | 0.6662 | 0.6640 | 0.6667 | 0.6653 | |
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| 0.1675 | 4.0 | 2172 | 1.5271 | 0.6621 | 0.6612 | 0.6699 | 0.6593 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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