--- library_name: transformers license: cc-by-nc-4.0 base_model: facebook/mms-1b-all tags: - automatic-speech-recognition - nyagen - mms - generated_from_trainer metrics: - wer model-index: - name: mms-1b-nyagen-male-model results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # mms-1b-nyagen-male-model This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NYAGEN - BEM dataset. It achieves the following results on the evaluation set: - Loss: 0.1298 - Wer: 0.1952 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Use 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: 100 - num_epochs: 30.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | 6.345 | 0.2463 | 100 | 0.4506 | 0.4026 | | 0.353 | 0.4926 | 200 | 0.2066 | 0.2924 | | 0.2989 | 0.7389 | 300 | 0.1829 | 0.2715 | | 0.2402 | 0.9852 | 400 | 0.1674 | 0.2546 | | 0.2302 | 1.2315 | 500 | 0.1582 | 0.2436 | | 0.2279 | 1.4778 | 600 | 0.1602 | 0.2428 | | 0.2264 | 1.7241 | 700 | 0.1507 | 0.2287 | | 0.2276 | 1.9704 | 800 | 0.1496 | 0.2353 | | 0.2088 | 2.2167 | 900 | 0.1460 | 0.2208 | | 0.1881 | 2.4631 | 1000 | 0.1455 | 0.2165 | | 0.2079 | 2.7094 | 1100 | 0.1418 | 0.2168 | | 0.196 | 2.9557 | 1200 | 0.1404 | 0.2086 | | 0.1782 | 3.2020 | 1300 | 0.1373 | 0.2078 | | 0.1741 | 3.4483 | 1400 | 0.1343 | 0.1944 | | 0.1948 | 3.6946 | 1500 | 0.1318 | 0.2137 | | 0.1904 | 3.9409 | 1600 | 0.1307 | 0.2043 | | 0.1762 | 4.1872 | 1700 | 0.1313 | 0.2003 | | 0.1718 | 4.4335 | 1800 | 0.1275 | 0.1932 | | 0.1595 | 4.6798 | 1900 | 0.1276 | 0.1952 | | 0.1811 | 4.9261 | 2000 | 0.1290 | 0.1983 | | 0.1477 | 5.1724 | 2100 | 0.1298 | 0.1952 | ### Framework versions - Transformers 4.48.0.dev0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0