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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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- hi |
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- model_for_talk |
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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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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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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 7 |
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type: mozilla-foundation/common_voice_7_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: 100 |
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- name: Test CER |
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type: cer |
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value: 92.98 |
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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-hindi |
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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: 0.5414 |
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- Wer: 1.0194 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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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| 4.6095 | 3.38 | 500 | 4.5881 | 0.9999 | |
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| 3.3396 | 6.76 | 1000 | 3.3301 | 1.0001 | |
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| 2.0061 | 10.14 | 1500 | 1.2096 | 1.0063 | |
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| 1.523 | 13.51 | 2000 | 0.7836 | 1.0051 | |
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| 1.3868 | 16.89 | 2500 | 0.6837 | 1.0080 | |
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| 1.2807 | 20.27 | 3000 | 0.6568 | 1.0112 | |
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| 1.231 | 23.65 | 3500 | 0.6120 | 1.0105 | |
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| 1.1673 | 27.03 | 4000 | 0.5972 | 1.0089 | |
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| 1.1416 | 30.41 | 4500 | 0.5780 | 1.0132 | |
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| 1.0738 | 33.78 | 5000 | 0.5806 | 1.0123 | |
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| 1.0771 | 37.16 | 5500 | 0.5586 | 1.0067 | |
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| 1.0287 | 40.54 | 6000 | 0.5464 | 1.0058 | |
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| 1.0106 | 43.92 | 6500 | 0.5407 | 1.0062 | |
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| 0.9538 | 47.3 | 7000 | 0.5334 | 1.0089 | |
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| 0.9607 | 50.68 | 7500 | 0.5395 | 1.0110 | |
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| 0.9108 | 54.05 | 8000 | 0.5502 | 1.0137 | |
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| 0.9252 | 57.43 | 8500 | 0.5498 | 1.0062 | |
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| 0.8943 | 60.81 | 9000 | 0.5448 | 1.0158 | |
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| 0.8728 | 64.19 | 9500 | 0.5257 | 1.0113 | |
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| 0.8577 | 67.57 | 10000 | 0.5550 | 1.0178 | |
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| 0.8332 | 70.95 | 10500 | 0.5607 | 1.0166 | |
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| 0.8174 | 74.32 | 11000 | 0.5429 | 1.0145 | |
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| 0.8168 | 77.7 | 11500 | 0.5561 | 1.0116 | |
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| 0.7872 | 81.08 | 12000 | 0.5478 | 1.0164 | |
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| 0.7707 | 84.46 | 12500 | 0.5412 | 1.0216 | |
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| 0.7742 | 87.84 | 13000 | 0.5391 | 1.0207 | |
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| 0.7594 | 91.22 | 13500 | 0.5379 | 1.0208 | |
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| 0.7678 | 94.59 | 14000 | 0.5415 | 1.0198 | |
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| 0.7502 | 97.97 | 14500 | 0.5409 | 1.0191 | |
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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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