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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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- go_emotions |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: electricidad-base-finetuned-go_emotions-es-2 |
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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: go_emotions |
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type: go_emotions |
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config: simplified |
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split: train |
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args: simplified |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5591468777484608 |
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- name: F1 |
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type: f1 |
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value: 0.5581665299693344 |
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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-base-finetuned-go_emotions-es-2 |
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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 go_emotions dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0837 |
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- Accuracy: 0.5591 |
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- F1: 0.5582 |
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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: 64 |
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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 | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 1.7525 | 1.0 | 2270 | 1.6088 | 0.5618 | 0.5076 | |
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| 1.4522 | 2.0 | 4540 | 1.4687 | 0.5807 | 0.5534 | |
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| 1.2798 | 3.0 | 6810 | 1.4550 | 0.5910 | 0.5773 | |
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| 1.0825 | 4.0 | 9080 | 1.5068 | 0.5873 | 0.5726 | |
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| 0.9214 | 5.0 | 11350 | 1.6168 | 0.5776 | 0.5743 | |
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| 0.7696 | 6.0 | 13620 | 1.7338 | 0.5776 | 0.5722 | |
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| 0.6688 | 7.0 | 15890 | 1.8733 | 0.5631 | 0.5596 | |
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| 0.553 | 8.0 | 18160 | 1.9571 | 0.5574 | 0.5591 | |
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| 0.4626 | 9.0 | 20430 | 2.0499 | 0.5646 | 0.5625 | |
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| 0.4399 | 10.0 | 22700 | 2.0837 | 0.5591 | 0.5582 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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