--- license: apache-2.0 tags: - generated_from_trainer datasets: - financial_phrasebank metrics: - accuracy - f1 model-index: - name: distilbert-base-uncased_allagree3 results: - task: name: Text Classification type: text-classification dataset: name: financial_phrasebank type: financial_phrasebank args: sentences_allagree metrics: - name: Accuracy type: accuracy value: 0.9778761061946902 - name: F1 type: f1 value: 0.9780006392634297 --- # distilbert-base-uncased_allagree3 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset. It achieves the following results on the evaluation set: - Loss: 0.0937 - Accuracy: 0.9779 - F1: 0.9780 ## 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: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.6418 | 1.0 | 57 | 0.3340 | 0.8805 | 0.8768 | | 0.1821 | 2.0 | 114 | 0.1088 | 0.9690 | 0.9691 | | 0.0795 | 3.0 | 171 | 0.0822 | 0.9823 | 0.9823 | | 0.0385 | 4.0 | 228 | 0.0939 | 0.9646 | 0.9646 | | 0.0218 | 5.0 | 285 | 0.1151 | 0.9735 | 0.9737 | | 0.0149 | 6.0 | 342 | 0.1126 | 0.9690 | 0.9694 | | 0.006 | 7.0 | 399 | 0.0989 | 0.9779 | 0.9780 | | 0.0093 | 8.0 | 456 | 0.1009 | 0.9779 | 0.9780 | | 0.0063 | 9.0 | 513 | 0.0899 | 0.9779 | 0.9780 | | 0.0039 | 10.0 | 570 | 0.0937 | 0.9779 | 0.9780 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.11.0+cpu - Datasets 2.3.2 - Tokenizers 0.12.1