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--- |
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language: |
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- hi |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_7_0 |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-1b-hi-cv7 |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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type: mozilla-foundation/common_voice_7_0 |
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name: Common Voice 7 |
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args: hi |
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metrics: |
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- type: wer |
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value: 18.504 |
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name: Test WER |
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- name: Test CER |
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type: cer |
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value: 6.655 |
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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-xls-r-1b-hi-cv7 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5878 |
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- Wer: 0.3419 |
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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: 7.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 2000 |
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- num_epochs: 100.0 |
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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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| 1.9859 | 2.72 | 400 | 1.1663 | 0.7948 | |
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| 1.2969 | 5.44 | 800 | 0.7725 | 0.6562 | |
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| 1.1954 | 8.16 | 1200 | 0.5940 | 0.4904 | |
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| 1.164 | 10.88 | 1600 | 0.5338 | 0.4316 | |
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| 1.1464 | 13.6 | 2000 | 0.5432 | 0.4226 | |
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| 1.1553 | 16.33 | 2400 | 0.5471 | 0.4260 | |
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| 1.0985 | 19.05 | 2800 | 0.5290 | 0.4076 | |
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| 1.0421 | 21.77 | 3200 | 0.5672 | 0.4181 | |
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| 0.9831 | 24.49 | 3600 | 0.5741 | 0.4141 | |
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| 0.9827 | 27.21 | 4000 | 0.5754 | 0.4179 | |
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| 0.9669 | 29.93 | 4400 | 0.5310 | 0.3889 | |
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| 0.9496 | 32.65 | 4800 | 0.5649 | 0.4062 | |
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| 0.9112 | 35.37 | 5200 | 0.5738 | 0.3926 | |
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| 0.8838 | 38.1 | 5600 | 0.5232 | 0.3768 | |
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| 0.8666 | 40.81 | 6000 | 0.5510 | 0.3852 | |
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| 0.8366 | 43.54 | 6400 | 0.5436 | 0.3837 | |
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| 0.7957 | 46.26 | 6800 | 0.5337 | 0.3775 | |
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| 0.7834 | 48.98 | 7200 | 0.5611 | 0.3844 | |
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| 0.7685 | 51.7 | 7600 | 0.5710 | 0.4008 | |
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| 0.7431 | 54.42 | 8000 | 0.5636 | 0.3726 | |
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| 0.7353 | 57.14 | 8400 | 0.5937 | 0.3836 | |
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| 0.7001 | 59.86 | 8800 | 0.5815 | 0.3858 | |
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| 0.6799 | 62.58 | 9200 | 0.5862 | 0.3696 | |
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| 0.6459 | 65.31 | 9600 | 0.6181 | 0.3762 | |
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| 0.6121 | 68.03 | 10000 | 0.5637 | 0.3590 | |
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| 0.5942 | 70.75 | 10400 | 0.6374 | 0.3882 | |
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| 0.5769 | 73.47 | 10800 | 0.6015 | 0.3640 | |
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| 0.5689 | 76.19 | 11200 | 0.5669 | 0.3508 | |
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| 0.5461 | 78.91 | 11600 | 0.5967 | 0.3621 | |
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| 0.5286 | 81.63 | 12000 | 0.5840 | 0.3605 | |
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| 0.5057 | 84.35 | 12400 | 0.5848 | 0.3489 | |
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| 0.482 | 87.07 | 12800 | 0.5860 | 0.3488 | |
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| 0.4655 | 89.79 | 13200 | 0.5780 | 0.3453 | |
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| 0.4523 | 92.52 | 13600 | 0.6150 | 0.3532 | |
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| 0.4422 | 95.24 | 14000 | 0.5930 | 0.3452 | |
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| 0.4436 | 97.96 | 14400 | 0.5867 | 0.3428 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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#### Evaluation Commands |
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1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test` |
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```bash |
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python eval.py --model_id anuragshas/wav2vec2-xls-r-1b-hi --dataset mozilla-foundation/common_voice_7_0 --config hi --split test |
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``` |
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### Inference With LM |
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```python |
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import torch |
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from datasets import load_dataset |
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from transformers import AutoModelForCTC, AutoProcessor |
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import torchaudio.functional as F |
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model_id = "anuragshas/wav2vec2-xls-r-1b-hi" |
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sample_iter = iter(load_dataset("mozilla-foundation/common_voice_7_0", "hi", split="test", streaming=True, use_auth_token=True)) |
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sample = next(sample_iter) |
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resampled_audio = F.resample(torch.tensor(sample["audio"]["array"]), 48_000, 16_000).numpy() |
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model = AutoModelForCTC.from_pretrained(model_id) |
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processor = AutoProcessor.from_pretrained(model_id) |
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input_values = processor(resampled_audio, return_tensors="pt").input_values |
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with torch.no_grad(): |
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logits = model(input_values).logits |
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transcription = processor.batch_decode(logits.numpy()).text |
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# => "तुम्हारे पास तीन महीने बचे हैं" |
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``` |
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### Eval results on Common Voice 7 "test" (WER): |
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| Without LM | With LM (run `./eval.py`) | |
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|---|---| |
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| 28.942 | 18.504 | |
