Update README.md

README.md

@@ -39,6 +39,35 @@ The model uses the QuotaClimat/frugalaichallenge-text-train dataset:
 
 ## Performance
 
+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.
+
+## 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
+
 ### Metrics
 - **Accuracy**: ~12.5% (random chance with 8 classes)
 - **Environmental Impact**: