--- license: apache-2.0 tags: - generated_from_trainer datasets: - emotion metrics: - accuracy model-index: - name: distiled_flip_model_emotion_alpha_0.8_epoch7_v1 results: - task: name: Text Classification type: text-classification dataset: name: emotion type: emotion config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9435 --- # distiled_flip_model_emotion_alpha_0.8_epoch7_v1 This model is a fine-tuned version of [ArafatBHossain/distill_bert_fine_tuned_emotion_dataset](https://huggingface.co/ArafatBHossain/distill_bert_fine_tuned_emotion_dataset) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.1583 - Accuracy: 0.9435 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 7 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.2013 | 1.0 | 2000 | 0.2653 | 0.9355 | | 0.1625 | 2.0 | 4000 | 0.2537 | 0.9365 | | 0.1262 | 3.0 | 6000 | 0.1934 | 0.935 | | 0.1048 | 4.0 | 8000 | 0.1813 | 0.9435 | | 0.0777 | 5.0 | 10000 | 0.1500 | 0.941 | | 0.0614 | 6.0 | 12000 | 0.1591 | 0.944 | | 0.0465 | 7.0 | 14000 | 0.1583 | 0.9435 | ### Framework versions - Transformers 4.23.1 - Pytorch 1.11.0 - Datasets 2.6.1 - Tokenizers 0.12.1