results
This model is a fine-tuned version of michellejieli/emotion_text_classifier on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2828
- F1: 0.7879
- Roc Auc: nan
- Hamming: 0.1039
Model description
This model uses a lightweight RoBERTa checkpoint that has been fine-tuned on evaluating emotions to further be trained on recognizing climate disinformation.
Intended uses & limitations
To be used as a submission for the Frugal AI competition
Training and evaluation data
Dataset of text and labels available on Frugal AI competition page.
Training procedure
Used a binarizer to tokenize the text and found a seemingly suitable model checkpoint as a good place to start!
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for nhankins/frugal_ai_submission
Base model
michellejieli/emotion_text_classifier