--- license: apache-2.0 tags: - generated_from_trainer datasets: - tweet_eval metrics: - f1 model-index: - name: hate_trained_42 results: - task: name: Text Classification type: text-classification dataset: name: tweet_eval type: tweet_eval args: hate metrics: - name: F1 type: f1 value: 0.7712319060633668 --- # hate_trained_42 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. It achieves the following results on the evaluation set: - Loss: 0.8994 - F1: 0.7712 ## 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: 2.7272339744854407e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.4835 | 1.0 | 563 | 0.4855 | 0.7556 | | 0.3277 | 2.0 | 1126 | 0.5354 | 0.7704 | | 0.2112 | 3.0 | 1689 | 0.6870 | 0.7751 | | 0.1384 | 4.0 | 2252 | 0.8994 | 0.7712 | ### Framework versions - Transformers 4.12.5 - Pytorch 1.9.1 - Datasets 1.16.1 - Tokenizers 0.10.3