--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: distilbert_finetune_own_data_model results: [] --- # distilbert_finetune_own_data_model This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0052 - Precision: 1.0 - Recall: 1.0 - F1: 1.0 - Accuracy: 1.0 ## 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: 8 - eval_batch_size: 8 - 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 | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 18 | 0.0907 | 0.8889 | 1.0 | 0.9412 | 0.9706 | | No log | 2.0 | 36 | 0.0119 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 3.0 | 54 | 0.0114 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 4.0 | 72 | 0.0141 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 5.0 | 90 | 0.0055 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 6.0 | 108 | 0.0044 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 7.0 | 126 | 0.0040 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 8.0 | 144 | 0.0043 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 9.0 | 162 | 0.0049 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 10.0 | 180 | 0.0052 | 1.0 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2