--- license: apache-2.0 tags: - generated_from_trainer datasets: - tweet_eval metrics: - accuracy - f1 model-index: - name: mini-mlm-imdb-target-tweet results: - task: name: Text Classification type: text-classification dataset: name: tweet_eval type: tweet_eval config: emotion split: train args: emotion metrics: - name: Accuracy type: accuracy value: 0.767379679144385 - name: F1 type: f1 value: 0.7668830990510893 --- # mini-mlm-imdb-target-tweet This model is a fine-tuned version of [muhtasham/mini-mlm-imdb](https://huggingface.co/muhtasham/mini-mlm-imdb) on the tweet_eval dataset. It achieves the following results on the evaluation set: - Loss: 1.3042 - Accuracy: 0.7674 - F1: 0.7669 ## 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: 3e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - num_epochs: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.8543 | 4.9 | 500 | 0.6920 | 0.7674 | 0.7571 | | 0.3797 | 9.8 | 1000 | 0.7231 | 0.7727 | 0.7709 | | 0.1668 | 14.71 | 1500 | 0.9171 | 0.7594 | 0.7583 | | 0.068 | 19.61 | 2000 | 1.1558 | 0.7647 | 0.7642 | | 0.0409 | 24.51 | 2500 | 1.3042 | 0.7674 | 0.7669 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.12.1 - Datasets 2.7.1 - Tokenizers 0.13.2