--- library_name: transformers license: mit base_model: facebook/w2v-bert-2.0 tags: - generated_from_trainer model-index: - name: w2v-bert-2.0_dyula results: [] --- # w2v-bert-2.0_dyula This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 0.1112 - eval_cer: 0.0312 - eval_wer: 0.1146 - eval_runtime: 34.6853 - eval_samples_per_second: 17.385 - eval_steps_per_second: 2.191 - epoch: 1.9430 - step: 3000 ## 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: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 800 - num_epochs: 32 - mixed_precision_training: Native AMP ### Framework versions - Transformers 4.55.2 - Pytorch 2.6.0+cu124 - Datasets 2.14.5 - Tokenizers 0.21.4