--- license: apache-2.0 base_model: distilbert/distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-financial-time-period results: [] --- # distilbert-financial-time-period This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4592 - Accuracy: 0.8730 - F1: 0.8700 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 6 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 1.7259 | 1.0 | 159 | 1.0685 | 0.6984 | 0.6205 | | 0.6121 | 2.0 | 318 | 0.4579 | 0.8889 | 0.8832 | | 0.1625 | 3.0 | 477 | 0.4437 | 0.8730 | 0.8734 | | 0.0558 | 4.0 | 636 | 0.4504 | 0.8730 | 0.8700 | | 0.0326 | 5.0 | 795 | 0.4623 | 0.8889 | 0.8873 | | 0.0257 | 6.0 | 954 | 0.4592 | 0.8730 | 0.8700 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1