--- license: apache-2.0 base_model: distilbert/distilbert-base-multilingual-cased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: trained_serbian results: [] --- # trained_serbian This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0786 - Precision: 0.8138 - Recall: 0.8795 - F1: 0.8454 - Accuracy: 0.9774 ## 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 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 104 | 0.1030 | 0.7317 | 0.7706 | 0.7507 | 0.9667 | | No log | 2.0 | 208 | 0.0814 | 0.8001 | 0.8642 | 0.8309 | 0.9757 | | No log | 3.0 | 312 | 0.0786 | 0.8138 | 0.8795 | 0.8454 | 0.9774 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2+cpu - Datasets 2.18.0 - Tokenizers 0.15.2