--- license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: distilbert-base-multilingual-cased-finetuned-psi-classification-oversampled-gpu results: [] --- # distilbert-base-multilingual-cased-finetuned-psi-classification-oversampled-gpu This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0669 - Accuracy: 0.9855 - F1: 0.9855 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.402 | 1.0 | 1076 | 0.1036 | 0.9710 | 0.9705 | | 0.1002 | 2.0 | 2152 | 0.0758 | 0.9779 | 0.9775 | | 0.0517 | 3.0 | 3228 | 0.0839 | 0.9779 | 0.9780 | | 0.0363 | 4.0 | 4304 | 0.0718 | 0.9855 | 0.9855 | | 0.0307 | 5.0 | 5380 | 0.0669 | 0.9855 | 0.9855 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1