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--- |
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language: |
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- hsb |
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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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- hsb |
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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-hsb-v1 |
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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: hsb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.4393 |
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- name: Test CER |
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type: cer |
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value: 0.1036 |
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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: hsb |
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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-hsb-v1 |
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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 - HSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5684 |
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- Wer: 0.4402 |
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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-hsb-v1 --dataset mozilla-foundation/common_voice_8_0 --config hsb --split test --log_outputs |
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2. To evaluate on speech-recognition-community-v2/dev_data |
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Upper Sorbian language isn't available in speech-recognition-community-v2/dev_data |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00045 |
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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: 500 |
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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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| 8.972 | 3.23 | 100 | 3.7498 | 1.0 | |
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| 3.3401 | 6.45 | 200 | 3.2320 | 1.0 | |
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| 3.2046 | 9.68 | 300 | 3.1741 | 0.9806 | |
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| 2.4031 | 12.9 | 400 | 1.0579 | 0.8996 | |
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| 1.0427 | 16.13 | 500 | 0.7989 | 0.7557 | |
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| 0.741 | 19.35 | 600 | 0.6405 | 0.6299 | |
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| 0.5699 | 22.58 | 700 | 0.6129 | 0.5928 | |
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| 0.4607 | 25.81 | 800 | 0.6548 | 0.5695 | |
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| 0.3827 | 29.03 | 900 | 0.6268 | 0.5190 | |
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| 0.3282 | 32.26 | 1000 | 0.5919 | 0.5016 | |
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| 0.2764 | 35.48 | 1100 | 0.5953 | 0.4805 | |
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| 0.2335 | 38.71 | 1200 | 0.5717 | 0.4728 | |
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| 0.2106 | 41.94 | 1300 | 0.5674 | 0.4569 | |
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| 0.1859 | 45.16 | 1400 | 0.5685 | 0.4502 | |
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| 0.1592 | 48.39 | 1500 | 0.5684 | 0.4402 | |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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