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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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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-mms-1b-even-pakendorf |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.7591335595927331 |
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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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# wav2vec2-large-mms-1b-even-pakendorf |
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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 audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.7591 |
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- Cer: 0.2779 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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- 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 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| 1.847 | 0.1895 | 300 | inf | 0.9027 | 0.3662 | |
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| 1.8253 | 0.3790 | 600 | inf | 0.9087 | 0.3658 | |
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| 1.6956 | 0.5685 | 900 | inf | 0.8723 | 0.3412 | |
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| 1.6616 | 0.7581 | 1200 | inf | 0.8437 | 0.3209 | |
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| 1.5962 | 0.9476 | 1500 | inf | 0.8392 | 0.3217 | |
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| 1.6299 | 1.1371 | 1800 | inf | 0.8447 | 0.3201 | |
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| 1.5242 | 1.3266 | 2100 | inf | 0.8191 | 0.3076 | |
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| 1.582 | 1.5161 | 2400 | inf | 0.8157 | 0.3070 | |
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| 1.5555 | 1.7056 | 2700 | inf | 0.8092 | 0.3061 | |
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| 1.5476 | 1.8951 | 3000 | inf | 0.7999 | 0.3009 | |
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| 1.4725 | 2.0846 | 3300 | inf | 0.7945 | 0.2952 | |
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| 1.4902 | 2.2742 | 3600 | inf | 0.7834 | 0.2936 | |
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| 1.3984 | 2.4637 | 3900 | inf | 0.7836 | 0.2900 | |
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| 1.4633 | 2.6532 | 4200 | inf | 0.7942 | 0.2872 | |
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| 1.4533 | 2.8427 | 4500 | inf | 0.7804 | 0.2863 | |
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| 1.4814 | 3.0322 | 4800 | inf | 0.7728 | 0.2859 | |
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| 1.4397 | 3.2217 | 5100 | inf | 0.7693 | 0.2818 | |
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| 1.4218 | 3.4112 | 5400 | inf | 0.7702 | 0.2831 | |
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| 1.3655 | 3.6008 | 5700 | inf | 0.7650 | 0.2795 | |
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| 1.34 | 3.7903 | 6000 | inf | 0.7615 | 0.2792 | |
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| 1.3351 | 3.9798 | 6300 | inf | 0.7591 | 0.2779 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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