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--- |
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language: |
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- hu |
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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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- hu |
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- model_for_talk |
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- mozilla-foundation/common_voice_8_0 |
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- robust-speech-event |
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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: Akashpb13/xlsr_hungarian_new |
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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: hu |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.2851621517163838 |
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- name: Test CER |
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type: cer |
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value: 0.06112982522287432 |
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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: hu |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.2851621517163838 |
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- name: Test CER |
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type: cer |
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value: 0.06112982522287432 |
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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 - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: hu |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 47.15 |
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--- |
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# Akashpb13/xlsr_hungarian_new |
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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 - hu dataset. |
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It achieves the following results on evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other and dev datasets): |
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- Loss: 0.197464 |
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- Wer: 0.330094 |
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## Model description |
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"facebook/wav2vec2-xls-r-300m" was finetuned. |
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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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Training data - |
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Common voice hungarian train.tsv, dev.tsv, invalidated.tsv, reported.tsv, and other.tsv |
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Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0 |
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## Training procedure |
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For creating the train dataset, all possible datasets were appended and 90-10 split was used. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.000095637994662983496 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 13 |
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- gradient_accumulation_steps: 16 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Step | Training Loss | Validation Loss | Wer | |
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|------|---------------|-----------------|----------| |
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| 500 | 4.785300 | 0.952295 | 0.796236 | |
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| 1000 | 0.535800 | 0.217474 | 0.381613 | |
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| 1500 | 0.258400 | 0.205524 | 0.345056 | |
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| 2000 | 0.202800 | 0.198680 | 0.336264 | |
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| 2500 | 0.182700 | 0.197464 | 0.330094 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.10.3 |
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#### Evaluation Commands |
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1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test` |
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```bash |
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python eval.py --model_id Akashpb13/xlsr_hungarian_new --dataset mozilla-foundation/common_voice_8_0 --config hu --split test |
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``` |
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