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nsalahaddinov
/
whisper-large-v3-az

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Azerbaijani
whisper
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
nsalahaddinov commited on
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1 Parent(s): 763d08e

End of training

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Files changed (5) hide show
  1. README.md +11 -11
  2. generation_config.json +1 -1
  3. model-00001-of-00002.safetensors +1 -1
  4. model-00002-of-00002.safetensors +1 -1
  5. runs/Jun01_14-56-43_8a38d76a00b5/events.out.tfevents.1717253806.8a38d76a00b5.3425.0 +2 -2
README.md CHANGED
@@ -24,7 +24,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 28.68525896414343
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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
@@ -34,8 +34,8 @@ 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 17.0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5938
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- - Wer: 28.6853
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  ## Model description
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@@ -66,18 +66,18 @@ The following hyperparameters were used during training:
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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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- | 0.0 | 142.8571 | 1000 | 0.4999 | 27.4900 |
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- | 0.0 | 285.7143 | 2000 | 0.5441 | 28.2869 |
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- | 0.0 | 428.5714 | 3000 | 0.5710 | 28.2869 |
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- | 0.0 | 571.4286 | 4000 | 0.5869 | 28.6853 |
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- | 0.0 | 714.2857 | 5000 | 0.5938 | 28.6853 |
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  ### Framework versions
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- - Transformers 4.41.1
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 38.645418326693225
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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 17.0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1394
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+ - Wer: 38.6454
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  ## Model description
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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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+ | 0.0408 | 3.3670 | 1000 | 0.8681 | 38.2470 |
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+ | 0.0094 | 6.7340 | 2000 | 1.0290 | 39.8406 |
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+ | 0.0012 | 10.1010 | 3000 | 1.0423 | 39.0438 |
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+ | 0.0004 | 13.4680 | 4000 | 1.1243 | 38.6454 |
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+ | 0.0002 | 16.8350 | 5000 | 1.1394 | 38.6454 |
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  ### Framework versions
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+ - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
generation_config.json CHANGED
@@ -253,5 +253,5 @@
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  "transcribe": 50360,
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  "translate": 50359
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  },
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- "transformers_version": "4.41.1"
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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": "4.41.2"
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  }
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