--- license: apache-2.0 tags: - generated_from_trainer datasets: - tweet_eval metrics: - accuracy - f1 model-index: - name: mini-mlm-tweet-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: 0.7352941176470589 - name: F1 type: f1 value: 0.737654460370971 --- # mini-mlm-tweet-target-tweet This model is a fine-tuned version of [muhtasham/mini-mlm-tweet](https://huggingface.co/muhtasham/mini-mlm-tweet) on the tweet_eval dataset. It achieves the following results on the evaluation set: - Loss: 1.4122 - Accuracy: 0.7353 - F1: 0.7377 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.8264 | 4.9 | 500 | 0.7479 | 0.7219 | 0.7190 | | 0.3705 | 9.8 | 1000 | 0.8205 | 0.7487 | 0.7479 | | 0.1775 | 14.71 | 1500 | 1.0049 | 0.7273 | 0.7286 | | 0.092 | 19.61 | 2000 | 1.1698 | 0.7353 | 0.7351 | | 0.0513 | 24.51 | 2500 | 1.4122 | 0.7353 | 0.7377 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.12.1 - Datasets 2.7.1 - Tokenizers 0.13.2