--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-yahd results: [] --- # distilbert-base-uncased-finetuned-yahd 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: 2.8670 - Accuracy: 0.1863 ## 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: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.6746 | 1.0 | 919 | 2.5961 | 0.1324 | | 2.3991 | 2.0 | 1838 | 2.5052 | 0.1448 | | 2.036 | 3.0 | 2757 | 2.5028 | 0.1554 | | 1.6838 | 4.0 | 3676 | 2.6002 | 0.1614 | | 1.3583 | 5.0 | 4595 | 2.7135 | 0.1783 | | 1.17 | 6.0 | 5514 | 2.8161 | 0.1787 | | 1.0365 | 7.0 | 6433 | 2.8670 | 0.1863 | ### Framework versions - Transformers 4.12.3 - Pytorch 1.9.0+cu102 - Datasets 1.15.1 - Tokenizers 0.10.3