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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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- mozilla-foundation/common_voice_9_0 |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_9_0 |
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metrics: |
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- wer |
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model-index: |
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- name: XLS-R-300M - Hindi |
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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_9_0 |
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name: Common Voice 9 |
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args: hi |
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metrics: |
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- type: wer |
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value: 21.145 |
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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: 7.709 |
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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_9_0 - HI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5164 |
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- Wer: 0.3349 |
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- Cer: 0.1082 |
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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: 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: 9815 |
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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 | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| 3.9471 | 8.16 | 400 | 3.7109 | 1.0 | 1.0 | |
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| 3.274 | 16.32 | 800 | 3.1582 | 0.9917 | 0.9573 | |
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| 1.5889 | 24.48 | 1200 | 0.7763 | 0.6030 | 0.1990 | |
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| 1.3647 | 32.65 | 1600 | 0.6051 | 0.5135 | 0.1687 | |
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| 1.2532 | 40.81 | 2000 | 0.5423 | 0.4712 | 0.1539 | |
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| 1.1905 | 48.97 | 2400 | 0.5180 | 0.4532 | 0.1490 | |
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| 1.1193 | 57.14 | 2800 | 0.4906 | 0.4248 | 0.1393 | |
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| 1.0584 | 65.3 | 3200 | 0.4854 | 0.4069 | 0.1332 | |
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| 1.0095 | 73.46 | 3600 | 0.4780 | 0.3926 | 0.1287 | |
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| 0.9759 | 81.63 | 4000 | 0.4666 | 0.3925 | 0.1269 | |
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| 0.9593 | 89.79 | 4400 | 0.4808 | 0.3830 | 0.1247 | |
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| 0.909 | 97.95 | 4800 | 0.4798 | 0.3765 | 0.1212 | |
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| 0.8788 | 106.12 | 5200 | 0.4906 | 0.3608 | 0.1162 | |
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| 0.8471 | 114.28 | 5600 | 0.4759 | 0.3604 | 0.1166 | |
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| 0.8116 | 122.44 | 6000 | 0.5080 | 0.3627 | 0.1176 | |
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| 0.7881 | 130.61 | 6400 | 0.4868 | 0.3489 | 0.1135 | |
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| 0.766 | 138.77 | 6800 | 0.4955 | 0.3492 | 0.1136 | |
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| 0.7333 | 146.93 | 7200 | 0.5019 | 0.3461 | 0.1125 | |
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| 0.709 | 155.1 | 7600 | 0.5084 | 0.3468 | 0.1117 | |
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| 0.6911 | 163.26 | 8000 | 0.5144 | 0.3412 | 0.1106 | |
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| 0.6683 | 171.42 | 8400 | 0.5219 | 0.3409 | 0.1117 | |
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| 0.659 | 179.59 | 8800 | 0.5230 | 0.3376 | 0.1096 | |
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| 0.6475 | 187.75 | 9200 | 0.5229 | 0.3398 | 0.1097 | |
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| 0.6419 | 195.91 | 9600 | 0.5200 | 0.3337 | 0.1084 | |
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### Framework versions |
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- Transformers 4.19.0.dev0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.1.1.dev0 |
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- Tokenizers 0.12.1 |
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