Baselhany commited on
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Model save

Browse files
README.md CHANGED
@@ -1,27 +1,25 @@
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  ---
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  library_name: transformers
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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-base
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  tags:
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  - generated_from_trainer
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper base AR - BA
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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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  should probably proofread and complete it, then remove this comment. -->
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- # Whisper base AR - BA
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- This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1260
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- - Wer: 0.2865
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  ## Model description
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@@ -49,7 +47,7 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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- - num_epochs: 15
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -71,6 +69,14 @@ The following hyperparameters were used during training:
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  | 2.0863 | 13.0 | 4069 | 0.1214 | 0.2672 |
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  | 2.0235 | 14.0 | 4382 | 0.1213 | 0.2638 |
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  | 2.015 | 14.9536 | 4680 | 0.1213 | 0.2626 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
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  library_name: transformers
 
 
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  license: apache-2.0
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+ base_model: Baselhany/Distilation_Whisper_base_CKP_10k
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  tags:
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  - generated_from_trainer
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  metrics:
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  - wer
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  model-index:
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+ - name: Distilation_Whisper_base_CKP_10k
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # Distilation_Whisper_base_CKP_10k
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+ This model is a fine-tuned version of [Baselhany/Distilation_Whisper_base_CKP_10k](https://huggingface.co/Baselhany/Distilation_Whisper_base_CKP_10k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1208
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+ - Wer: 0.2551
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 20
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  | 2.0863 | 13.0 | 4069 | 0.1214 | 0.2672 |
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  | 2.0235 | 14.0 | 4382 | 0.1213 | 0.2638 |
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  | 2.015 | 14.9536 | 4680 | 0.1213 | 0.2626 |
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+ | 7.0386 | 13.0 | 4875 | 0.1209 | 0.2760 |
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+ | 5.2638 | 14.0 | 5250 | 0.1169 | 0.2538 |
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+ | 3.8581 | 15.0 | 5625 | 0.1180 | 0.2374 |
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+ | 3.4661 | 16.0 | 6000 | 0.1176 | 0.2408 |
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+ | 2.8903 | 17.0 | 6375 | 0.1167 | 0.2359 |
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+ | 2.6081 | 18.0 | 6750 | 0.1172 | 0.2358 |
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+ | 2.6719 | 19.0 | 7125 | 0.1165 | 0.2401 |
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+ | 2.4235 | 20.0 | 7500 | 0.1160 | 0.2430 |
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  ### Framework versions
generation_config.json CHANGED
@@ -65,20 +65,7 @@
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  "init_std": 0.02,
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  "is_decoder": false,
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  "is_encoder_decoder": true,
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  "is_multilingual": true,
 
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  "1": "LABEL_1"
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  },
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  "init_std": 0.02,
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+ "input_ids": null,
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "is_decoder": false,
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  "is_encoder_decoder": true,
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  "is_multilingual": true,
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