--- license: mit base_model: Tommert25/robbert0410_lrate7.5b32 tags: - generated_from_trainer metrics: - recall - accuracy model-index: - name: robbert1010_lrate7.5b32 results: [] --- # robbert1010_lrate7.5b32 This model is a fine-tuned version of [Tommert25/robbert0410_lrate7.5b32](https://huggingface.co/Tommert25/robbert0410_lrate7.5b32) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5187 - Precisions: 0.8552 - Recall: 0.7999 - F-measure: 0.8232 - Accuracy: 0.9157 ## 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: 7.5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 6 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:| | 0.0496 | 1.0 | 118 | 0.5283 | 0.8488 | 0.7962 | 0.8132 | 0.9092 | | 0.0474 | 2.0 | 236 | 0.4726 | 0.7961 | 0.7965 | 0.7931 | 0.9075 | | 0.026 | 3.0 | 354 | 0.5187 | 0.8552 | 0.7999 | 0.8232 | 0.9157 | | 0.0145 | 4.0 | 472 | 0.5150 | 0.8372 | 0.7791 | 0.7998 | 0.9116 | | 0.0088 | 5.0 | 590 | 0.5250 | 0.8372 | 0.7818 | 0.8021 | 0.9141 | | 0.007 | 6.0 | 708 | 0.5299 | 0.8468 | 0.7849 | 0.8072 | 0.9162 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1