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End of training

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README.md CHANGED
@@ -1,59 +1,53 @@
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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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- - audio
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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: whisper-small-ar-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: mozilla-foundation/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: ar
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  metrics:
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  - name: Wer
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  type: wer
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- value: 158.15321276282899
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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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- # whisper-small-ar-v1
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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: 0.3354
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- - Wer: 158.1532
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  ## Model description
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- Whisper model fine-tuned on Arabic data, following the [official tutorial](https://huggingface.co/blog/fine-tune-whisper).
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  ## Intended uses & limitations
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- The model is not fully trained yet. Hence, it is not intended for professional use.
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  ## Training and evaluation data
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- Training Data: CommonVoice (v16.1) Arabic train + validation splits
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- Validation Data: CommonVoice (v16.1) Arabic test split
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  ## Training procedure
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@@ -62,12 +56,12 @@ Validation Data: CommonVoice (v16.1) Arabic test split
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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: 8
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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: 4000
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -78,11 +72,15 @@ The following hyperparameters were used during training:
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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 4.37.2
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- - Pytorch 2.2.0+cu121
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- - Datasets 2.17.0
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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
generation_config.json CHANGED
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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": "4.37.2"
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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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