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--- |
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language: |
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- hy-AM |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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- hy |
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datasets: |
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- common_voice |
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model-index: |
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- name: '' |
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results: [] |
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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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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HY-AM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5891 |
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- Wer: 0.6569 |
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**Note**: If you aim for best performance use [this model](https://huggingface.co/arampacha/wav2vec2-xls-r-300m-hy). It is trained using noizy student procedure and achieves considerably better results. |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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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_ratio: 0.1 |
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- training_steps: 1200 |
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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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| 9.167 | 16.67 | 100 | 3.5599 | 1.0 | |
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| 3.2645 | 33.33 | 200 | 3.1771 | 1.0 | |
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| 3.1509 | 50.0 | 300 | 3.1321 | 1.0 | |
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| 3.0757 | 66.67 | 400 | 2.8594 | 1.0 | |
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| 2.5274 | 83.33 | 500 | 1.5286 | 0.9797 | |
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| 1.6826 | 100.0 | 600 | 0.8058 | 0.7974 | |
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| 1.2868 | 116.67 | 700 | 0.6713 | 0.7279 | |
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| 1.1262 | 133.33 | 800 | 0.6308 | 0.7034 | |
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| 1.0408 | 150.0 | 900 | 0.6056 | 0.6745 | |
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| 0.9617 | 166.67 | 1000 | 0.5891 | 0.6569 | |
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| 0.9196 | 183.33 | 1100 | 0.5913 | 0.6432 | |
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| 0.8853 | 200.0 | 1200 | 0.5924 | 0.6347 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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