--- 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: 0.0004 - 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 3 | 0.6185 | 0.0 | 0.0 | 0.0 | 0.68 | | No log | 2.0 | 6 | 0.4919 | 0.0 | 0.0 | 0.0 | 0.68 | | No log | 3.0 | 9 | 0.3741 | 0.0 | 0.0 | 0.0 | 0.72 | | No log | 4.0 | 12 | 0.2685 | 1.0 | 0.8 | 0.8889 | 0.96 | | No log | 5.0 | 15 | 0.1781 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 6.0 | 18 | 0.1043 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 7.0 | 21 | 0.0556 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 8.0 | 24 | 0.0293 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 9.0 | 27 | 0.0163 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 10.0 | 30 | 0.0095 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 11.0 | 33 | 0.0059 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 12.0 | 36 | 0.0040 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 13.0 | 39 | 0.0028 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 14.0 | 42 | 0.0021 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 15.0 | 45 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 16.0 | 48 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 17.0 | 51 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 18.0 | 54 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 19.0 | 57 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 20.0 | 60 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 21.0 | 63 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 22.0 | 66 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 23.0 | 69 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 24.0 | 72 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 25.0 | 75 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 26.0 | 78 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 27.0 | 81 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 28.0 | 84 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 29.0 | 87 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 30.0 | 90 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 31.0 | 93 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 32.0 | 96 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 33.0 | 99 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 34.0 | 102 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 35.0 | 105 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 36.0 | 108 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 37.0 | 111 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 38.0 | 114 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 39.0 | 117 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 40.0 | 120 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 41.0 | 123 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 42.0 | 126 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 43.0 | 129 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 44.0 | 132 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 45.0 | 135 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 46.0 | 138 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 47.0 | 141 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 48.0 | 144 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 49.0 | 147 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 50.0 | 150 | 0.0004 | 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