--- license: mit base_model: neuraly/bert-base-italian-cased-sentiment tags: - generated_from_trainer datasets: - tweet_sentiment_multilingual metrics: - accuracy model-index: - name: sentiment_ita results: - task: name: Text Classification type: text-classification dataset: name: tweet_sentiment_multilingual type: tweet_sentiment_multilingual config: italian split: validation args: italian metrics: - name: Accuracy type: accuracy value: 0.6944444444444444 --- # sentiment_ita This model is a fine-tuned version of [neuraly/bert-base-italian-cased-sentiment](https://huggingface.co/neuraly/bert-base-italian-cased-sentiment) on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set: - Loss: 2.3610 - Accuracy: 0.6944 ## 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: 5e-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_steps: 800 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 171 | 0.7979 | 0.6574 | | 0.8861 | 2.0 | 342 | 0.7423 | 0.6944 | | 0.8861 | 3.0 | 513 | 0.8450 | 0.6914 | | 0.3208 | 4.0 | 684 | 1.2621 | 0.6698 | | 0.3208 | 5.0 | 855 | 1.3658 | 0.6790 | | 0.1361 | 6.0 | 1026 | 1.9379 | 0.6883 | | 0.1361 | 7.0 | 1197 | 2.2134 | 0.6667 | | 0.0567 | 8.0 | 1368 | 2.4013 | 0.6728 | | 0.0567 | 9.0 | 1539 | 2.3630 | 0.6914 | | 0.0113 | 10.0 | 1710 | 2.3610 | 0.6944 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.0.1 - Datasets 2.15.0 - Tokenizers 0.15.0