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--- |
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license: apache-2.0 |
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language: as |
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tags: |
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- audio |
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- automatic-speech-recognition |
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- speech |
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- xlsr-fine-tuning |
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- as |
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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-assamese |
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results: [] |
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--- |
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# wav2vec2-large-xls-r-300m-assamese |
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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 common_voice_7_0 dataset. |
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It achieves the following results on the evaluation set: |
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- WER: 0.7954545454545454 |
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- CER: 0.32341269841269843 |
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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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To compute the evaluation parameters |
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```bash |
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cd wav2vec2-large-xls-r-300m-odia; python eval.py --model_id ./ --dataset mozilla-foundation/common_voice_7_0 --config or --split test --log_outputs |
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``` |
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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: 3e-4 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: not given |
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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: 400 |
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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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| 1.584065 | NA | 400 | 1.584065 | 0.915512 | |
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| 1.658865 | Na | 800 | 1.658865 | 0.805096 | |
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| 1.882352 | NA | 1200 | 1.882352 | 0.820742 | |
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| 1.881240 | NA | 1600 | 1.881240 | 0.810907 | |
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| 2.159748 | NA | 2000 | 2.159748 | 0.804202 | |
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| 1.992871 | NA | 2400 | 1.992871 | 0.803308 | |
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| 2.201436 | NA | 2800 | 2.201436 | 0.802861 | |
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| 2.165218 | NA | 3200 | 2.165218 | 0.793920 | |
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| 2.253643 | NA | 3600 | 2.253643 | 0.796603 | |
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| 2.265880 | NA | 4000 | 2.265880 | 0.790344 | |
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| 2.293935 | NA | 4400 | 2.293935 | 0.797050 | |
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| 2.288851 | NA | 4800 | 2.288851 | 0.784086 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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