--- base_model: duraad/nep-spell-hft tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: nep-spell-hft-993-01-05 results: [] --- # nep-spell-hft-993-01-05 This model is a fine-tuned version of [duraad/nep-spell-hft](https://huggingface.co/duraad/nep-spell-hft) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: nan - Accuracy: 0.2828 - Precision: 0.2828 - Recall: 0.2828 - F1: 0.2828 ## 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: 1e-06 - train_batch_size: 6 - eval_batch_size: 6 - 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 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.0 | 0.75 | 100 | nan | 0.2828 | 0.2828 | 0.2828 | 0.2828 | | 0.0 | 1.5 | 200 | nan | 0.2828 | 0.2828 | 0.2828 | 0.2828 | | 0.0 | 2.26 | 300 | nan | 0.2828 | 0.2828 | 0.2828 | 0.2828 | | 0.0 | 3.01 | 400 | nan | 0.2828 | 0.2828 | 0.2828 | 0.2828 | | 0.0 | 3.76 | 500 | nan | 0.2828 | 0.2828 | 0.2828 | 0.2828 | | 0.0 | 4.51 | 600 | nan | 0.2828 | 0.2828 | 0.2828 | 0.2828 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2