--- license: apache-2.0 base_model: facebook/hubert-xlarge-ll60k tags: - generated_from_trainer metrics: - wer model-index: - name: hubert-xlarge-ll60k_arabic results: [] --- # hubert-xlarge-ll60k_arabic This model is a fine-tuned version of [facebook/hubert-xlarge-ll60k](https://huggingface.co/facebook/hubert-xlarge-ll60k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1133 - Wer: 0.6646 - Per: 0.6706 ## 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: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Per | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| | 13.7253 | 1.0 | 1637 | 3.3328 | 1.0 | 1.0 | | 3.3354 | 2.0 | 3274 | 3.2847 | 1.0 | 1.0 | | 3.304 | 3.0 | 4911 | 3.2375 | 1.0 | 1.0 | | 3.2655 | 4.0 | 6548 | 3.2143 | 1.0 | 1.0 | | 3.2242 | 5.0 | 8185 | 3.1874 | 1.0 | 1.0 | | 3.1556 | 6.0 | 9822 | 3.0734 | 1.0 | 1.0 | | 3.0485 | 7.0 | 11459 | 2.9548 | 1.0 | 1.0 | | 2.935 | 8.0 | 13096 | 2.8378 | 0.9043 | 0.9171 | | 2.8158 | 9.0 | 14733 | 2.7023 | 0.8971 | 0.9087 | | 2.7185 | 10.0 | 16370 | 2.5982 | 0.8865 | 0.8997 | | 2.6406 | 11.0 | 18007 | 2.5032 | 0.8453 | 0.8571 | | 2.5721 | 12.0 | 19644 | 2.4385 | 0.8179 | 0.8291 | | 2.5136 | 13.0 | 21281 | 2.3810 | 0.7994 | 0.8097 | | 2.457 | 14.0 | 22918 | 2.3041 | 0.7792 | 0.7896 | | 2.4104 | 15.0 | 24555 | 2.2466 | 0.7588 | 0.7695 | | 2.3711 | 16.0 | 26192 | 2.2066 | 0.7321 | 0.7417 | | 2.3365 | 17.0 | 27829 | 2.1757 | 0.7002 | 0.7072 | | 2.3109 | 18.0 | 29466 | 2.1412 | 0.6771 | 0.6828 | | 2.2857 | 19.0 | 31103 | 2.1265 | 0.6722 | 0.6785 | | 2.2757 | 20.0 | 32740 | 2.1133 | 0.6646 | 0.6706 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0