--- license: cc-by-nc-4.0 base_model: facebook/mms-1b-all tags: - generated_from_trainer datasets: - common_voice_6_1 metrics: - wer model-index: - name: wav2vec2-large-mms-1b-turkish-colab results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice_6_1 type: common_voice_6_1 config: tr split: test args: tr metrics: - name: Wer type: wer value: 0.21101011132672862 --- # wav2vec2-large-mms-1b-turkish-colab This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_6_1 dataset. It achieves the following results on the evaluation set: - Loss: 0.1472 - Wer: 0.2110 ## 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: 0.001 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 4.6395 | 0.92 | 100 | 0.1800 | 0.2494 | | 0.2845 | 1.83 | 200 | 0.1673 | 0.2354 | | 0.2692 | 2.75 | 300 | 0.1573 | 0.2227 | | 0.245 | 3.67 | 400 | 0.1568 | 0.2147 | | 0.2385 | 4.59 | 500 | 0.1533 | 0.2164 | | 0.2416 | 5.5 | 600 | 0.1502 | 0.2139 | | 0.2182 | 6.42 | 700 | 0.1507 | 0.2124 | | 0.2276 | 7.34 | 800 | 0.1472 | 0.2110 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3