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warmestman
/
whisper-large-v3-mn-cv-fleurs

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Mongolian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
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End of training

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Files changed (4) hide show
  1. README.md +19 -13
  2. generation_config.json +1 -1
  3. model-00001-of-00002.safetensors +1 -1
  4. model-00002-of-00002.safetensors +1 -1
README.md CHANGED
@@ -26,7 +26,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 33.65601452065343
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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
@@ -36,8 +36,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 & FLEURS dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4942
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- - Wer: 33.6560
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  ## Model description
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@@ -56,29 +56,35 @@ More information needed
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  ### Training hyperparameters
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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: 16
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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
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- | Training Loss | Epoch | Step | Validation Loss | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|
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- | 0.0361 | 5.99 | 1000 | 0.3833 | 42.0109 |
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- | 0.0016 | 11.98 | 2000 | 0.4445 | 37.2092 |
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- | 0.0002 | 17.96 | 3000 | 0.4784 | 34.0410 |
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- | 0.0001 | 23.95 | 4000 | 0.4942 | 33.6560 |
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.37.2
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- - Pytorch 1.12.1+cu116
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  - Datasets 2.17.0
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  - Tokenizers 0.15.2
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 31.994939772289754
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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 [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 & FLEURS dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5662
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+ - Wer: 31.9949
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 16
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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: 10000
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  - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|
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+ | 0.0691 | 5.99 | 1000 | 0.4597 | 41.5049 |
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+ | 0.0183 | 11.98 | 2000 | 0.4996 | 38.2982 |
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+ | 0.012 | 17.96 | 3000 | 0.5328 | 38.5402 |
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+ | 0.0091 | 23.95 | 4000 | 0.5619 | 38.1277 |
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+ | 0.004 | 29.94 | 5000 | 0.5439 | 35.2236 |
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+ | 0.0019 | 35.93 | 6000 | 0.5731 | 35.3941 |
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+ | 0.001 | 41.92 | 7000 | 0.5309 | 33.3755 |
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+ | 0.0002 | 47.9 | 8000 | 0.5391 | 32.3140 |
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+ | 0.0 | 53.89 | 9000 | 0.5543 | 32.1984 |
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+ | 0.0 | 59.88 | 10000 | 0.5662 | 31.9949 |
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  ### Framework versions
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+ - Transformers 4.38.0.dev0
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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
generation_config.json CHANGED
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  "transcribe": 50360,
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  "translate": 50359
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  },
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- "transformers_version": "4.37.2"
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  }
 
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  "transcribe": 50360,
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  "translate": 50359
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  },
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+ "transformers_version": "4.38.0.dev0"
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  }
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