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--- |
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language: |
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- or |
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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_8_0 |
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- generated_from_trainer |
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- or |
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- robust-speech-event |
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- model_for_talk |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-or-d5 |
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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: or |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.579136690647482 |
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- name: Test CER |
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type: cer |
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value: 0.1572148018392818 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: or |
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metrics: |
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- name: Test WER |
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type: wer |
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value: NA |
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- name: Test CER |
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type: cer |
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value: NA |
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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-or-d5 |
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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_8_0 - OR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9571 |
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- Wer: 0.5450 |
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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-or-d5 --dataset mozilla-foundation/common_voice_8_0 --config or --split test --log_outputs |
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2. To evaluate on speech-recognition-community-v2/dev_data |
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python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-or-d5 --dataset speech-recognition-community-v2/dev_data --config or --split validation --chunk_length_s 10 --stride_length_s 1 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.000111 |
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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: 800 |
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- num_epochs: 200 |
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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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| 9.2958 | 12.5 | 300 | 4.9014 | 1.0 | |
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| 3.4065 | 25.0 | 600 | 3.5150 | 1.0 | |
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| 1.5402 | 37.5 | 900 | 0.8356 | 0.7249 | |
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| 0.6049 | 50.0 | 1200 | 0.7754 | 0.6349 | |
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| 0.4074 | 62.5 | 1500 | 0.7994 | 0.6217 | |
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| 0.3097 | 75.0 | 1800 | 0.8815 | 0.5985 | |
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| 0.2593 | 87.5 | 2100 | 0.8532 | 0.5754 | |
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| 0.2097 | 100.0 | 2400 | 0.9077 | 0.5648 | |
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| 0.1784 | 112.5 | 2700 | 0.9047 | 0.5668 | |
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| 0.1567 | 125.0 | 3000 | 0.9019 | 0.5728 | |
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| 0.1315 | 137.5 | 3300 | 0.9295 | 0.5827 | |
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| 0.1125 | 150.0 | 3600 | 0.9256 | 0.5681 | |
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| 0.1035 | 162.5 | 3900 | 0.9148 | 0.5496 | |
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| 0.0901 | 175.0 | 4200 | 0.9480 | 0.5483 | |
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| 0.0817 | 187.5 | 4500 | 0.9799 | 0.5516 | |
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| 0.079 | 200.0 | 4800 | 0.9571 | 0.5450 | |
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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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