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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_8_0 |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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metrics: |
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- wer |
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model-index: |
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- name: XLS-R-1B - Hindi |
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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: Common Voice 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: hi |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 15.899 |
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- name: Test CER |
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type: cer |
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value: 5.83 |
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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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# XLS-R-1B - Hindi |
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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_8_0 - HI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6921 |
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- Wer: 0.3547 |
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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: 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: 1500 |
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- num_epochs: 50.0 |
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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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| 2.0674 | 2.07 | 400 | 1.3411 | 0.8835 | |
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| 1.324 | 4.15 | 800 | 0.9311 | 0.7142 | |
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| 1.2023 | 6.22 | 1200 | 0.8060 | 0.6170 | |
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| 1.1573 | 8.29 | 1600 | 0.7415 | 0.4972 | |
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| 1.1117 | 10.36 | 2000 | 0.7248 | 0.4588 | |
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| 1.0672 | 12.44 | 2400 | 0.6729 | 0.4350 | |
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| 1.0336 | 14.51 | 2800 | 0.7117 | 0.4346 | |
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| 1.0025 | 16.58 | 3200 | 0.7019 | 0.4272 | |
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| 0.9578 | 18.65 | 3600 | 0.6792 | 0.4118 | |
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| 0.9272 | 20.73 | 4000 | 0.6863 | 0.4156 | |
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| 0.9321 | 22.8 | 4400 | 0.6535 | 0.3972 | |
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| 0.8802 | 24.87 | 4800 | 0.6766 | 0.3906 | |
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| 0.844 | 26.94 | 5200 | 0.6782 | 0.3949 | |
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| 0.8387 | 29.02 | 5600 | 0.6916 | 0.3921 | |
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| 0.8042 | 31.09 | 6000 | 0.6806 | 0.3797 | |
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| 0.793 | 33.16 | 6400 | 0.7120 | 0.3831 | |
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| 0.7567 | 35.23 | 6800 | 0.6862 | 0.3808 | |
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| 0.7463 | 37.31 | 7200 | 0.6893 | 0.3709 | |
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| 0.7053 | 39.38 | 7600 | 0.7096 | 0.3701 | |
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| 0.6906 | 41.45 | 8000 | 0.6921 | 0.3676 | |
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| 0.6891 | 43.52 | 8400 | 0.7167 | 0.3663 | |
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| 0.658 | 45.6 | 8800 | 0.6833 | 0.3580 | |
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| 0.6576 | 47.67 | 9200 | 0.6914 | 0.3569 | |
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| 0.6358 | 49.74 | 9600 | 0.6922 | 0.3551 | |
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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_8_0` with split `test` |
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```bash |
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python eval.py --model_id anuragshas/wav2vec2-xls-r-1b-hi-with-lm --dataset mozilla-foundation/common_voice_8_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-with-lm" |
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sample_iter = iter(load_dataset("mozilla-foundation/common_voice_8_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 8 "test" (WER): |
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| Without LM | With LM (run `./eval.py`) | |
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|---|---| |
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| 26.209 | 15.899 | |
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