--- language: - sk license: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_7_0 - generated_from_trainer - sk - robust-speech-event - model_for_talk - hf-asr-leaderboard datasets: - mozilla-foundation/common_voice_7_0 model-index: - name: XLS-R-300M - Slovak results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 7 type: mozilla-foundation/common_voice_7_0 args: sk metrics: - name: Test WER type: wer value: 24.852 - name: Test CER type: cer value: 5.09 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: sk metrics: - name: Test WER type: wer value: 56.388 - name: Test CER type: cer value: 20.654 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: sk metrics: - name: Test WER type: wer value: 59.25 --- # wav2vec2-large-xls-r-300m-slovak This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SK dataset. It achieves the following results on the evaluation set: - Loss: 0.2915 - Wer: 0.2481 ## 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: 7e-05 - train_batch_size: 32 - eval_batch_size: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 3000 - num_epochs: 100.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 1.0076 | 19.74 | 3000 | 0.3274 | 0.3806 | | 0.6889 | 39.47 | 6000 | 0.2824 | 0.2942 | | 0.5863 | 59.21 | 9000 | 0.2700 | 0.2735 | | 0.4798 | 78.95 | 12000 | 0.2844 | 0.2602 | | 0.4399 | 98.68 | 15000 | 0.2907 | 0.2489 | ### Framework versions - Transformers 4.16.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.17.1.dev0 - Tokenizers 0.11.0