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update model card README.md
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README.md
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---
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language:
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- ar
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license: apache-2.0
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tags:
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- robust-speech-event
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datasets:
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metrics:
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- wer
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- cer
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model-index:
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- name: wav2vec2-
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results:
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- task:
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type: automatic-speech-recognition # Required. Example: automatic-speech-recognition
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name: Speech Recognition # Optional. Example: Speech Recognition
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dataset:
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type: mozilla-foundation/common_voice_7_0 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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name: Common Voice ar # Required. Example: Common Voice zh-CN
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args: ar # Optional. Example: zh-CN
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metrics:
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- type: wer # Required. Example: wer
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value: 31.05 # Required. Example: 20.90
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name: Test WER # Optional. Example: Test WER
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args:
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- learning_rate: 0.0003
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- train_batch_size: 64
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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: 128
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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: 1000
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- num_epochs: 10
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- mixed_precision_training: Native AMP # Optional. Example for BLEU: max_order
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- type: cer # Required. Example: wer
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value: 8.78 # Required. Example: 20.90
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name: Test CER # Optional. Example: Test WER
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args:
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- learning_rate: 0.0003
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- train_batch_size: 64
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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: 128
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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: 1000
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- num_epochs: 10
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- mixed_precision_training: Native AMP # Optional. Example for BLEU: max_order
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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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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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- Cer: 0.
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## Training procedure
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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### Framework versions
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- Transformers 4.
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- Pytorch 1.10.
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- Datasets 1.
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- Tokenizers 0.11.0
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-large-xlsr-300-arabic
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results: []
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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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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4514
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- Wer: 0.4256
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- Cer: 0.1528
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## Model description
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More information needed
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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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More information needed
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## Training procedure
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 5.4375 | 1.8 | 500 | 3.3330 | 1.0 | 1.0 |
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| 2.2187 | 3.6 | 1000 | 0.7790 | 0.6501 | 0.2338 |
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| 0.9471 | 5.4 | 1500 | 0.5353 | 0.5015 | 0.1822 |
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| 0.7416 | 7.19 | 2000 | 0.4889 | 0.4490 | 0.1640 |
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| 0.6358 | 8.99 | 2500 | 0.4514 | 0.4256 | 0.1528 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2.dev0
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- Tokenizers 0.11.0
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