--- license: apache-2.0 base_model: distilbert-base-cased tags: - simplification - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: finetuned_model_sentiment_analysis_yelp results: [] --- # finetuned_model_sentiment_analysis_yelp This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the [yelp_review_full](https://huggingface.co/datasets/yelp_review_full) dataset. It achieves the following results on the evaluation set: - Loss: 0.8933 - Precision: 0.6404 - Recall: 0.6409 - F1: 0.6405 ## 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 - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:| | 0.8691 | 1.0 | 3657 | 0.8801 | 0.6224 | 0.6201 | 0.6149 | | 0.7506 | 2.0 | 7314 | 0.8469 | 0.6458 | 0.6421 | 0.6428 | | 0.6087 | 3.0 | 10971 | 0.8933 | 0.6404 | 0.6409 | 0.6405 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2