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--- |
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language: |
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- gn |
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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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- gn |
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- robust-speech-event |
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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-gn-k1 |
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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: gn |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.711890243902439 |
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- name: Test CER |
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type: cer |
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value: 0.13311897106109324 |
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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: gn |
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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-gn-k1 |
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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 - GN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9220 |
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- Wer: 0.6631 |
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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-gn-k1 --dataset mozilla-foundation/common_voice_8_0 --config gn --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: 0.00018 |
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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: 600 |
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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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| 15.9402 | 8.32 | 100 | 6.9185 | 1.0 | |
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| 4.6367 | 16.64 | 200 | 3.7416 | 1.0 | |
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| 3.4337 | 24.96 | 300 | 3.2581 | 1.0 | |
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| 3.2307 | 33.32 | 400 | 2.8008 | 1.0 | |
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| 1.3182 | 41.64 | 500 | 0.8359 | 0.8171 | |
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| 0.409 | 49.96 | 600 | 0.8470 | 0.8323 | |
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| 0.2573 | 58.32 | 700 | 0.7823 | 0.7576 | |
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| 0.1969 | 66.64 | 800 | 0.8306 | 0.7424 | |
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| 0.1469 | 74.96 | 900 | 0.9225 | 0.7713 | |
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| 0.1172 | 83.32 | 1000 | 0.7903 | 0.6951 | |
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| 0.1017 | 91.64 | 1100 | 0.8519 | 0.6921 | |
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| 0.0851 | 99.96 | 1200 | 0.8129 | 0.6646 | |
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| 0.071 | 108.32 | 1300 | 0.8614 | 0.7043 | |
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| 0.061 | 116.64 | 1400 | 0.8414 | 0.6921 | |
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| 0.0552 | 124.96 | 1500 | 0.8649 | 0.6905 | |
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| 0.0465 | 133.32 | 1600 | 0.8575 | 0.6646 | |
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| 0.0381 | 141.64 | 1700 | 0.8802 | 0.6723 | |
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| 0.0338 | 149.96 | 1800 | 0.8731 | 0.6845 | |
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| 0.0306 | 158.32 | 1900 | 0.9003 | 0.6585 | |
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| 0.0236 | 166.64 | 2000 | 0.9408 | 0.6616 | |
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| 0.021 | 174.96 | 2100 | 0.9353 | 0.6723 | |
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| 0.0212 | 183.32 | 2200 | 0.9269 | 0.6570 | |
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| 0.0191 | 191.64 | 2300 | 0.9277 | 0.6662 | |
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| 0.0161 | 199.96 | 2400 | 0.9220 | 0.6631 | |
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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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