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wav2vec2-mms-1b-all-swc-kat6

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +129 -0
  2. adapter.swc.safetensors +3 -0
  3. pytorch_model.bin +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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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-mms-1b-all-swc-kat6
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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: 0.37098445595854923
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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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+ # wav2vec2-mms-1b-all-swc-kat6
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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 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: 0.3710
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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: 1
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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: 400
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+ - num_epochs: 4
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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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+ | 2.8349 | 0.07 | 400 | inf | 0.4899 |
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+ | 0.8039 | 0.15 | 800 | inf | 0.4912 |
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+ | 0.7335 | 0.22 | 1200 | inf | 0.4482 |
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+ | 0.8395 | 0.3 | 1600 | inf | 0.4829 |
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+ | 0.7626 | 0.37 | 2000 | inf | 0.4635 |
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+ | 0.9035 | 0.44 | 2400 | inf | 0.4391 |
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+ | 0.6281 | 0.52 | 2800 | inf | 0.4668 |
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+ | 0.6756 | 0.59 | 3200 | inf | 0.4254 |
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+ | 0.7866 | 0.67 | 3600 | inf | 0.4168 |
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+ | 0.7413 | 0.74 | 4000 | inf | 0.4168 |
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+ | 0.749 | 0.81 | 4400 | inf | 0.4148 |
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+ | 0.8165 | 0.89 | 4800 | inf | 0.4241 |
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+ | 0.7302 | 0.96 | 5200 | inf | 0.4124 |
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+ | 0.7376 | 1.04 | 5600 | inf | 0.4368 |
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+ | 0.6833 | 1.11 | 6000 | inf | 0.3953 |
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+ | 0.6463 | 1.19 | 6400 | inf | 0.4363 |
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+ | 0.7236 | 1.26 | 6800 | inf | 0.4383 |
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+ | 0.8837 | 1.33 | 7200 | inf | 0.4811 |
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+ | 0.6854 | 1.41 | 7600 | inf | 0.3930 |
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+ | 0.6985 | 1.48 | 8000 | inf | 0.3979 |
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+ | 0.7139 | 1.56 | 8400 | inf | 0.3977 |
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+ | 0.6338 | 1.63 | 8800 | inf | 0.4039 |
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+ | 0.7227 | 1.7 | 9200 | inf | 0.3922 |
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+ | 0.6843 | 1.78 | 9600 | inf | 0.4111 |
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+ | 0.6948 | 1.85 | 10000 | inf | 0.4093 |
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+ | 0.6867 | 1.93 | 10400 | inf | 0.3927 |
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+ | 0.5753 | 2.0 | 10800 | inf | 0.4080 |
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+ | 0.6865 | 2.07 | 11200 | inf | 0.3938 |
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+ | 0.6155 | 2.15 | 11600 | inf | 0.3920 |
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+ | 0.6743 | 2.22 | 12000 | inf | 0.3977 |
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+ | 0.5801 | 2.3 | 12400 | inf | 0.3801 |
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+ | 0.8216 | 2.37 | 12800 | inf | 0.3917 |
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+ | 0.6199 | 2.44 | 13200 | inf | 0.4052 |
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+ | 0.6268 | 2.52 | 13600 | inf | 0.3811 |
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+ | 0.6505 | 2.59 | 14000 | inf | 0.3855 |
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+ | 0.6578 | 2.67 | 14400 | inf | 0.3933 |
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+ | 0.6442 | 2.74 | 14800 | inf | 0.3868 |
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+ | 0.5904 | 2.81 | 15200 | inf | 0.3782 |
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+ | 0.6249 | 2.89 | 15600 | inf | 0.3788 |
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+ | 0.5879 | 2.96 | 16000 | inf | 0.3904 |
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+ | 0.4844 | 3.04 | 16400 | inf | 0.3728 |
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+ | 0.6309 | 3.11 | 16800 | inf | 0.3687 |
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+ | 0.5825 | 3.19 | 17200 | inf | 0.3663 |
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+ | 0.7171 | 3.26 | 17600 | inf | 0.3772 |
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+ | 0.5471 | 3.33 | 18000 | inf | 0.3718 |
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+ | 0.5029 | 3.41 | 18400 | inf | 0.3756 |
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+ | 0.5605 | 3.48 | 18800 | inf | 0.3751 |
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+ | 0.5582 | 3.56 | 19200 | inf | 0.3728 |
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+ | 0.6358 | 3.63 | 19600 | inf | 0.3712 |
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+ | 0.4977 | 3.7 | 20000 | inf | 0.3655 |
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+ | 0.4828 | 3.78 | 20400 | inf | 0.3671 |
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+ | 0.6554 | 3.85 | 20800 | inf | 0.3689 |
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+ | 0.561 | 3.93 | 21200 | inf | 0.3702 |
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+ | 0.5515 | 4.0 | 21600 | inf | 0.3710 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0.dev0
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.13.1
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+ - Tokenizers 0.12.1
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