--- license: apache-2.0 base_model: facebook/wav2vec2-xls-r-300m tags: - generated_from_trainer datasets: - common_voice metrics: - wer model-index: - name: wav2vec2-large-xls-r-300m-euskera-colab results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice type: common_voice config: eu split: test args: eu metrics: - name: Wer type: wer value: 0.17522160918337998 --- # wav2vec2-large-xls-r-300m-euskera-colab This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. It achieves the following results on the evaluation set: - Loss: 0.1873 - Wer: 0.1752 ## 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: 0.0003 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 2.5827 | 0.76 | 600 | 0.3985 | 0.5778 | | 0.2963 | 1.51 | 1200 | 0.2492 | 0.4142 | | 0.2122 | 2.27 | 1800 | 0.2132 | 0.3133 | | 0.1686 | 3.03 | 2400 | 0.2078 | 0.2851 | | 0.1373 | 3.79 | 3000 | 0.1910 | 0.2750 | | 0.1254 | 4.54 | 3600 | 0.1850 | 0.2619 | | 0.1137 | 5.3 | 4200 | 0.1874 | 0.2503 | | 0.1008 | 6.06 | 4800 | 0.1857 | 0.2554 | | 0.0934 | 6.81 | 5400 | 0.1844 | 0.2404 | | 0.0876 | 7.57 | 6000 | 0.2001 | 0.2375 | | 0.0801 | 8.33 | 6600 | 0.2036 | 0.2512 | | 0.0732 | 9.09 | 7200 | 0.1921 | 0.2301 | | 0.069 | 9.84 | 7800 | 0.1821 | 0.2330 | | 0.0628 | 10.6 | 8400 | 0.1915 | 0.2249 | | 0.0619 | 11.36 | 9000 | 0.1881 | 0.2113 | | 0.0549 | 12.11 | 9600 | 0.1920 | 0.2076 | | 0.0524 | 12.87 | 10200 | 0.1901 | 0.2079 | | 0.0492 | 13.63 | 10800 | 0.1767 | 0.2020 | | 0.0445 | 14.38 | 11400 | 0.1852 | 0.1933 | | 0.0427 | 15.14 | 12000 | 0.1995 | 0.1994 | | 0.0398 | 15.9 | 12600 | 0.1922 | 0.1932 | | 0.037 | 16.66 | 13200 | 0.1956 | 0.1920 | | 0.0353 | 17.41 | 13800 | 0.1990 | 0.1909 | | 0.0327 | 18.17 | 14400 | 0.1906 | 0.1784 | | 0.0311 | 18.93 | 15000 | 0.1847 | 0.1765 | | 0.0295 | 19.68 | 15600 | 0.1873 | 0.1752 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3