--- library_name: transformers license: mit base_model: xlnet/xlnet-large-cased tags: - generated_from_trainer model-index: - name: cs221-xlnet-large-cased-finetuned results: [] --- # cs221-xlnet-large-cased-finetuned This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5859 - Bce Loss: 0.5859 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bce Loss | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6082 | 1.0 | 139 | 0.5886 | 0.5886 | | 0.5565 | 2.0 | 278 | 0.5873 | 0.5873 | | 0.5705 | 3.0 | 417 | 0.5873 | 0.5873 | | 0.5569 | 4.0 | 556 | 0.5859 | 0.5859 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.4.0 - Datasets 3.0.1 - Tokenizers 0.21.0