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  1. README.md +86 -0
  2. breeze-listen-w2v2-ml.log +2 -0
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ base_model: facebook/mms-1b-all
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_16_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: breeze-listen-w2v2-ml
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: common_voice_16_0
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+ type: common_voice_16_0
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+ config: ml
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+ split: test
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+ args: ml
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.5345542501727713
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # breeze-listen-w2v2-ml
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+
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+ This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_16_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2698
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+ - Wer: 0.5346
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 4.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 0.41 | 200 | 5.4728 | 1.0757 |
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+ | No log | 0.81 | 400 | 5.1274 | 1.0038 |
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+ | 6.5037 | 1.22 | 600 | 0.6167 | 0.8131 |
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+ | 6.5037 | 1.63 | 800 | 0.3284 | 0.5829 |
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+ | 1.0482 | 2.03 | 1000 | 0.3169 | 0.5667 |
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+ | 1.0482 | 2.44 | 1200 | 0.2876 | 0.5425 |
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+ | 1.0482 | 2.85 | 1400 | 0.2847 | 0.5522 |
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+ | 0.4314 | 3.25 | 1600 | 0.2746 | 0.5394 |
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+ | 0.4314 | 3.66 | 1800 | 0.2698 | 0.5346 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.0.dev0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
breeze-listen-w2v2-ml.log CHANGED
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  {'eval_loss': 0.2846720516681671, 'eval_wer': 0.5521769177608846, 'eval_runtime': 161.8788, 'eval_samples_per_second': 4.096, 'eval_steps_per_second': 0.513, 'epoch': 2.85}
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  {'loss': 0.4314, 'learning_rate': 0.00025374732334047106, 'epoch': 3.05}
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  {'eval_loss': 0.27460750937461853, 'eval_wer': 0.5393918451969593, 'eval_runtime': 160.7333, 'eval_samples_per_second': 4.125, 'eval_steps_per_second': 0.516, 'epoch': 3.25}
 
 
 
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  {'eval_loss': 0.2846720516681671, 'eval_wer': 0.5521769177608846, 'eval_runtime': 161.8788, 'eval_samples_per_second': 4.096, 'eval_steps_per_second': 0.513, 'epoch': 2.85}
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  {'loss': 0.4314, 'learning_rate': 0.00025374732334047106, 'epoch': 3.05}
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  {'eval_loss': 0.27460750937461853, 'eval_wer': 0.5393918451969593, 'eval_runtime': 160.7333, 'eval_samples_per_second': 4.125, 'eval_steps_per_second': 0.516, 'epoch': 3.25}
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+ {'eval_loss': 0.26981213688850403, 'eval_wer': 0.5345542501727713, 'eval_runtime': 160.1257, 'eval_samples_per_second': 4.14, 'eval_steps_per_second': 0.518, 'epoch': 3.66}
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+ {'train_runtime': 5112.0325, 'train_samples_per_second': 1.54, 'train_steps_per_second': 0.385, 'train_loss': 2.1205503649827913, 'epoch': 4.0}
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