--- license: apache-2.0 base_model: distilbert/distilbert-base-cased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-cased-clickbait-task1-20-epoch-post_title results: [] --- # distilbert-base-cased-clickbait-task1-20-epoch-post_title This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.4958 - Accuracy: 0.6475 ## 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: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 200 | 0.8537 | 0.6225 | | No log | 2.0 | 400 | 0.8157 | 0.65 | | 0.8073 | 3.0 | 600 | 0.8731 | 0.6525 | | 0.8073 | 4.0 | 800 | 0.9890 | 0.6825 | | 0.3328 | 5.0 | 1000 | 1.2191 | 0.6325 | | 0.3328 | 6.0 | 1200 | 1.4974 | 0.675 | | 0.3328 | 7.0 | 1400 | 1.7291 | 0.6575 | | 0.0842 | 8.0 | 1600 | 1.9302 | 0.65 | | 0.0842 | 9.0 | 1800 | 2.0243 | 0.66 | | 0.0262 | 10.0 | 2000 | 2.1548 | 0.6525 | | 0.0262 | 11.0 | 2200 | 2.3360 | 0.64 | | 0.0262 | 12.0 | 2400 | 2.2967 | 0.655 | | 0.0088 | 13.0 | 2600 | 2.2970 | 0.6525 | | 0.0088 | 14.0 | 2800 | 2.3359 | 0.6425 | | 0.0058 | 15.0 | 3000 | 2.4252 | 0.6525 | | 0.0058 | 16.0 | 3200 | 2.4796 | 0.6575 | | 0.0058 | 17.0 | 3400 | 2.4698 | 0.645 | | 0.0033 | 18.0 | 3600 | 2.4963 | 0.645 | | 0.0033 | 19.0 | 3800 | 2.4821 | 0.6475 | | 0.0022 | 20.0 | 4000 | 2.4958 | 0.6475 | ### Framework versions - Transformers 4.44.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1