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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- voxpopuli |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-classic-300m-norwegian-colab-hung |
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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: voxpopuli |
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type: voxpopuli |
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config: fi |
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split: test |
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args: fi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.7882131661442007 |
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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-classic-300m-norwegian-colab-hung |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the voxpopuli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.8820 |
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- Wer: 1.7882 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 500 |
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- num_epochs: 30 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 4.7686 | 2.57 | 400 | 2.9953 | 1.0 | |
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| 2.5005 | 5.14 | 800 | 2.2739 | 1.9808 | |
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| 1.6554 | 7.72 | 1200 | 2.4720 | 1.6708 | |
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| 1.1995 | 10.29 | 1600 | 2.2613 | 1.2480 | |
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| 0.8972 | 12.86 | 2000 | 2.7599 | 1.8873 | |
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| 0.6962 | 15.43 | 2400 | 3.2783 | 1.9560 | |
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| 0.5554 | 18.01 | 2800 | 3.2272 | 1.7544 | |
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| 0.4234 | 20.58 | 3200 | 3.0755 | 1.5645 | |
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| 0.3341 | 23.15 | 3600 | 3.5022 | 1.7442 | |
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| 0.2832 | 25.72 | 4000 | 3.7905 | 1.8324 | |
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| 0.2293 | 28.3 | 4400 | 3.8820 | 1.7882 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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