--- tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: finetuned_twitter_sentiment_LSTM results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # finetuned_twitter_sentiment_LSTM This model is a fine-tuned version of [LYTinn/lstm-finetuning-sentiment-model-3000-samples](https://huggingface.co/LYTinn/lstm-finetuning-sentiment-model-3000-samples) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9053 - Accuracy: 0.5551 - F1: 0.5509 - Precision: 0.5633 - Recall: 0.5551 ## 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: 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: 10 ### Training results ### Framework versions - Transformers 4.24.0 - Pytorch 1.12.1+cu113 - Datasets 2.7.0 - Tokenizers 0.13.2