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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-es-mt |
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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 |
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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-es-mt |
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type: go_emotions-es-mt |
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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: 0.5934476693051891 |
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- name: F1 |
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type: f1 |
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value: 0.5806237685841615 |
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widget: |
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- text: "Me gusta mucho su forma de ser" |
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- text: "Es una persona muy extraña..." |
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- text: "El dolor es desesperante" |
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- text: "No me esperaba una evolución tan positiva" |
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- text: "¡Dios mío, es enorme!" |
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- text: "¡Agg! Está asqueroso." |
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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 |
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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-es-mt](https://huggingface.co/datasets/mrm8488/go_emotions-es-mt) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5111 |
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- Accuracy: 0.5934 |
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- F1: 0.5806 |
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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: 5 |
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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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| 1.729 | 1.0 | 2270 | 1.5835 | 0.5578 | 0.5044 | |
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| 1.4432 | 2.0 | 4540 | 1.4529 | 0.5842 | 0.5538 | |
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| 1.2688 | 3.0 | 6810 | 1.4445 | 0.5945 | 0.5770 | |
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| 1.1017 | 4.0 | 9080 | 1.4804 | 0.5937 | 0.5781 | |
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| 0.9999 | 5.0 | 11350 | 1.5111 | 0.5934 | 0.5806 | |
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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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