End of training
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README.md
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---
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license: apache-2.0
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base_model: openai/whisper-small
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tags:
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- automatic-speech-recognition
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datasets:
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- mozilla-foundation/common_voice_16_1
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metrics:
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- wer
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widget:
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- example_title: Sample 1
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src: sample_ar.mp3
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model-index:
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- name:
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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:
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type: mozilla-foundation/common_voice_16_1
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config: ar
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split: test
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args: ar
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metrics:
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- name: Wer
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type: wer
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value:
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language:
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- ar
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library_name: transformers
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pipeline_tag: automatic-speech-recognition
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---
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This model is for Arabic automatic speech recognition (ASR). It is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Arabic portion of the `mozilla-foundation/common_voice_16_1` 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:
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## Model description
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## Intended uses & limitations
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-
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## Training and evaluation data
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Validation Data: CommonVoice (v16.1) Arabic test split
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## Training procedure
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 32
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- eval_batch_size:
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- seed: 42
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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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- training_steps:
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- mixed_precision_training: Native AMP
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### Training results
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| 0.1625 | 1.65 | 2000 | 0.3353 | 228.5252 |
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| 0.1002 | 2.47 | 3000 | 0.3311 | 238.8858 |
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| 0.0751 | 3.3 | 4000 | 0.3354 | 158.1532 |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.
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- Datasets 2.17.
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- Tokenizers 0.15.2
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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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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_16_1
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metrics:
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- wer
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model-index:
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- name: Whisper Small AR v.2
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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 16.1
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type: mozilla-foundation/common_voice_16_1
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config: ar
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split: test
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args: 'config: ar, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 47.726437288634024
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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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# Whisper Small AR v.2
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4007
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- Wer: 47.7264
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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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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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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- training_steps: 8000
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- mixed_precision_training: Native AMP
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### Training results
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| 0.1625 | 1.65 | 2000 | 0.3353 | 228.5252 |
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| 0.1002 | 2.47 | 3000 | 0.3311 | 238.8858 |
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| 0.0751 | 3.3 | 4000 | 0.3354 | 158.1532 |
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| 0.0601 | 4.12 | 5000 | 0.3576 | 48.9285 |
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| 0.0612 | 4.95 | 6000 | 0.3575 | 47.8937 |
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| 0.0383 | 5.77 | 7000 | 0.3819 | 46.9085 |
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| 0.0234 | 6.6 | 8000 | 0.4007 | 47.7264 |
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### Framework versions
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- Transformers 4.38.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.17.1
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- Tokenizers 0.15.2
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generation_config.json
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"<|yo|>": 50325,
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"<|zh|>": 50260
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},
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"max_initial_timestamp_index": 50,
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"max_length": 448,
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"no_timestamps_token_id": 50363,
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"transcribe": 50359,
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"translate": 50358
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},
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"transformers_version": "4.
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}
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"<|yo|>": 50325,
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"<|zh|>": 50260
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},
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"language": "ar",
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"max_initial_timestamp_index": 50,
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"max_length": 448,
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"no_timestamps_token_id": 50363,
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"transcribe": 50359,
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"translate": 50358
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},
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"transformers_version": "4.38.1"
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}
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model.safetensors
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runs/Feb24_23-41-48_326117fcf43d/events.out.tfevents.1708818121.326117fcf43d.12625.5
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