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whisper_romanian4

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README.md CHANGED
@@ -25,7 +25,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 40.8272994479891
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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
@@ -35,8 +35,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Romanian voice 1.0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2790
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- - Wer: 40.8273
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  ## Model description
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@@ -62,16 +62,18 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: constant_with_warmup
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  - lr_scheduler_warmup_steps: 50
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- - training_steps: 4000
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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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- | 0.0198 | 1.8 | 1000 | 0.2202 | 28.2171 |
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- | 0.0078 | 3.6 | 2000 | 0.2415 | 35.1244 |
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- | 0.0014 | 5.4 | 3000 | 0.2587 | 36.7517 |
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- | 0.0033 | 7.19 | 4000 | 0.2790 | 40.8273 |
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 23.876263531435946
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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-small](https://huggingface.co/openai/whisper-small) on the Romanian voice 1.0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2557
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+ - Wer: 23.8763
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: constant_with_warmup
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  - lr_scheduler_warmup_steps: 50
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+ - training_steps: 1500
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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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+ | 0.0156 | 0.45 | 250 | 0.2336 | 24.4175 |
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+ | 0.011 | 0.9 | 500 | 0.2361 | 25.0627 |
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+ | 0.0061 | 1.35 | 750 | 0.2479 | 27.5539 |
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+ | 0.0084 | 1.8 | 1000 | 0.2491 | 27.3174 |
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+ | 0.0054 | 2.25 | 1250 | 0.2532 | 21.1234 |
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+ | 0.0041 | 2.7 | 1500 | 0.2557 | 23.8763 |
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  ### Framework versions
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