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README.md
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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/
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- generated_from_trainer
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- hu
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- robust-speech-event
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- model_for_talk
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datasets:
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- mozilla-foundation/
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model-index:
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- name: Akashpb13/xlsr_hungarian_new
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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
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type: mozilla-foundation/
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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.
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- name: Test CER
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type: cer
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value: 0.
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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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metrics:
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- name: Test WER
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type: wer
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value: 0.
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- name: Test CER
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type: cer
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value: 0.
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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_7_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
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- Loss: 0.
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- Wer: 0.
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## Model description
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"facebook/wav2vec2-xls-r-300m" was finetuned.
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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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- total_train_batch_size: 316
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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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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### Training results
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Step | Training Loss | Validation Loss | Wer
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500 | 4.
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1000 | 0.
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1500 | 0.
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2000 | 0.
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2500 | 0.
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3500 | 0.161500 | 0.179107 | 0.299935
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4000 | 0.151700 | 0.183371 | 0.295283
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4500 | 0.143700 | 0.184443 | 0.295283
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5000 | 0.138900 | 0.184265 | 0.292771
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-
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### Framework versions
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- Transformers 4.16.0.dev0
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#### Evaluation Commands
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1. To evaluate on `mozilla-foundation/
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```bash
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python eval.py --model_id Akashpb13/xlsr_hungarian_new --dataset mozilla-foundation/
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```
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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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- hu
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- robust-speech-event
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- model_for_talk
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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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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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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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---
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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_7_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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- 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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### 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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#### 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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