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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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- hf-asr-leaderboard |
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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-large-xls-r-300m-hi-wx1 |
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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: 37.19684845500431 |
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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: 11.763235514672798 |
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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-large-xls-r-300m-hi-wx1 |
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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_7_0 -HI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6552 |
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- Wer: 0.3200 |
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Evaluation Commands |
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1. To evaluate on mozilla-foundation/common_voice_8_0 with test split |
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python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1 --dataset mozilla-foundation/common_voice_7_0 --config hi --split test --log_outputs |
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2. To evaluate on speech-recognition-community-v2/dev_data |
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NA |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00024 |
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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: 1800 |
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- num_epochs: 50 |
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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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| 12.2663 | 1.36 | 200 | 5.9245 | 1.0 | |
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| 4.1856 | 2.72 | 400 | 3.4968 | 1.0 | |
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| 3.3908 | 4.08 | 600 | 2.9970 | 1.0 | |
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| 1.5444 | 5.44 | 800 | 0.9071 | 0.6139 | |
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| 0.7237 | 6.8 | 1000 | 0.6508 | 0.4862 | |
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| 0.5323 | 8.16 | 1200 | 0.6217 | 0.4647 | |
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| 0.4426 | 9.52 | 1400 | 0.5785 | 0.4288 | |
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| 0.3933 | 10.88 | 1600 | 0.5935 | 0.4217 | |
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| 0.3532 | 12.24 | 1800 | 0.6358 | 0.4465 | |
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| 0.3319 | 13.6 | 2000 | 0.5789 | 0.4118 | |
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| 0.2877 | 14.96 | 2200 | 0.6163 | 0.4056 | |
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| 0.2663 | 16.33 | 2400 | 0.6176 | 0.3893 | |
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| 0.2511 | 17.68 | 2600 | 0.6065 | 0.3999 | |
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| 0.2275 | 19.05 | 2800 | 0.6183 | 0.3842 | |
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| 0.2098 | 20.41 | 3000 | 0.6486 | 0.3864 | |
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| 0.1943 | 21.77 | 3200 | 0.6365 | 0.3885 | |
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| 0.1877 | 23.13 | 3400 | 0.6013 | 0.3677 | |
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| 0.1679 | 24.49 | 3600 | 0.6451 | 0.3795 | |
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| 0.1667 | 25.85 | 3800 | 0.6410 | 0.3635 | |
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| 0.1514 | 27.21 | 4000 | 0.6000 | 0.3577 | |
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| 0.1453 | 28.57 | 4200 | 0.6020 | 0.3518 | |
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| 0.134 | 29.93 | 4400 | 0.6531 | 0.3517 | |
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| 0.1354 | 31.29 | 4600 | 0.6874 | 0.3578 | |
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| 0.1224 | 32.65 | 4800 | 0.6519 | 0.3492 | |
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| 0.1199 | 34.01 | 5000 | 0.6553 | 0.3490 | |
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| 0.1077 | 35.37 | 5200 | 0.6621 | 0.3429 | |
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| 0.0997 | 36.73 | 5400 | 0.6641 | 0.3413 | |
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| 0.0964 | 38.09 | 5600 | 0.6722 | 0.3385 | |
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| 0.0931 | 39.45 | 5800 | 0.6365 | 0.3363 | |
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| 0.0944 | 40.81 | 6000 | 0.6454 | 0.3326 | |
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| 0.0862 | 42.18 | 6200 | 0.6497 | 0.3256 | |
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| 0.0848 | 43.54 | 6400 | 0.6599 | 0.3226 | |
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| 0.0793 | 44.89 | 6600 | 0.6625 | 0.3232 | |
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| 0.076 | 46.26 | 6800 | 0.6463 | 0.3186 | |
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| 0.0749 | 47.62 | 7000 | 0.6559 | 0.3225 | |
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| 0.0663 | 48.98 | 7200 | 0.6552 | 0.3200 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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