--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer model-index: - name: distilbert-finetuning results: [] --- # distilbert-finetuning 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: 0.8143 ## 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: 5e-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 - lr_scheduler_warmup_steps: 500 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.3746 | 1.0 | 53 | 0.8143 | | 0.3103 | 2.0 | 106 | 0.8207 | | 0.2205 | 3.0 | 159 | 0.8499 | | 0.0624 | 4.0 | 212 | 0.9009 | | 0.0873 | 5.0 | 265 | 1.1236 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1