--- base_model: facebook/mms-1b-all datasets: - common_voice_17_0 library_name: transformers license: cc-by-nc-4.0 metrics: - wer - bleu tags: - generated_from_trainer model-index: - name: wav2vec2-mms-1b-CV17.0-training_set_variations results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: common_voice_17_0 type: common_voice_17_0 config: ta split: validation args: ta metrics: - type: wer value: 1.0759957831049183 name: Wer - type: bleu value: 0.0 name: Bleu --- # wav2vec2-mms-1b-CV17.0-training_set_variations This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset. It achieves the following results on the evaluation set: - Loss: 6.3100 - Wer: 1.0760 - Cer: 0.7242 - Bleu: 0.0 ## 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: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.15 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu | |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:----:| | 13.5071 | 6.25 | 50 | 7.0048 | 1.0001 | 0.9823 | 0.0 | | 5.6893 | 12.5 | 100 | 5.2167 | 1.0000 | 0.9089 | 0.0 | | 4.3569 | 18.75 | 150 | 4.3516 | 1.0125 | 0.8661 | 0.0 | | 3.5211 | 25.0 | 200 | 3.5506 | 1.0269 | 0.8318 | 0.0 | | 3.2359 | 31.25 | 250 | 3.4822 | 1.0039 | 0.8458 | 0.0 | | 3.1004 | 37.5 | 300 | 3.5209 | 1.0086 | 0.8185 | 0.0 | | 2.9953 | 43.75 | 350 | 3.5498 | 1.0121 | 0.8104 | 0.0 | | 2.779 | 50.0 | 400 | 3.6218 | 1.0170 | 0.7777 | 0.0 | | 2.6019 | 56.25 | 450 | 4.0907 | 1.0134 | 0.7504 | 0.0 | | 2.4589 | 62.5 | 500 | 3.8633 | 1.0287 | 0.7476 | 0.0 | | 2.2318 | 68.75 | 550 | 3.7976 | 1.0367 | 0.7239 | 0.0 | | 2.0073 | 75.0 | 600 | 4.0050 | 1.0234 | 0.7288 | 0.0 | | 1.7416 | 81.25 | 650 | 4.2022 | 1.0126 | 0.7231 | 0.0 | | 1.5467 | 87.5 | 700 | 4.4087 | 1.0469 | 0.7197 | 0.0 | | 1.3716 | 93.75 | 750 | 4.5391 | 1.0471 | 0.7185 | 0.0 | | 1.2237 | 100.0 | 800 | 4.8405 | 1.0398 | 0.7152 | 0.0 | | 1.1216 | 106.25 | 850 | 5.0209 | 1.0421 | 0.7160 | 0.0 | | 1.0274 | 112.5 | 900 | 5.0349 | 1.0669 | 0.7160 | 0.0 | | 0.9325 | 118.75 | 950 | 5.2384 | 1.0500 | 0.7198 | 0.0 | | 0.8486 | 125.0 | 1000 | 5.3843 | 1.0614 | 0.7131 | 0.0 | | 0.7996 | 131.25 | 1050 | 5.4558 | 1.0622 | 0.7181 | 0.0 | | 0.7479 | 137.5 | 1100 | 5.6746 | 1.0622 | 0.7205 | 0.0 | | 0.6972 | 143.75 | 1150 | 5.7069 | 1.1182 | 0.7218 | 0.0 | | 0.6596 | 150.0 | 1200 | 5.7678 | 1.0883 | 0.7221 | 0.0 | | 0.6213 | 156.25 | 1250 | 5.9645 | 1.0700 | 0.7191 | 0.0 | | 0.5905 | 162.5 | 1300 | 6.0098 | 1.0970 | 0.7210 | 0.0 | | 0.5532 | 168.75 | 1350 | 6.0379 | 1.0981 | 0.7235 | 0.0 | | 0.5336 | 175.0 | 1400 | 6.2079 | 1.0564 | 0.7210 | 0.0 | | 0.4955 | 181.25 | 1450 | 6.1618 | 1.0717 | 0.7225 | 0.0 | | 0.4851 | 187.5 | 1500 | 6.3100 | 1.0760 | 0.7242 | 0.0 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1