--- license: mit base_model: microsoft/MiniLM-L12-H384-uncased tags: - generated_from_trainer datasets: - emotion metrics: - f1 model-index: - name: test01 results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion config: split split: validation args: split metrics: - name: F1 type: f1 value: 0.9104824364647098 --- # test01 This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.3902 - F1: 0.9105 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.4186 | 1.0 | 250 | 1.1125 | 0.4765 | | 0.9485 | 2.0 | 500 | 0.7212 | 0.8291 | | 0.6309 | 3.0 | 750 | 0.5014 | 0.8881 | | 0.4772 | 4.0 | 1000 | 0.4186 | 0.9122 | | 0.4078 | 5.0 | 1250 | 0.3902 | 0.9105 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.13.3