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JoshEe00
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whisper-tiny-minds14-en_US-test-finetuned

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End of training

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Files changed (3) hide show
  1. README.md +15 -8
  2. model.safetensors +1 -1
  3. runs/May14_14-51-29_mum-hpc2-gpu3/events.out.tfevents.1715669490.mum-hpc2-gpu3 +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 28.91705069124424
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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
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8974
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- - Wer Ortho: 30.4322
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- - Wer: 28.9171
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  ## Model description
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@@ -60,14 +60,21 @@ 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: 500
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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 Ortho | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
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- | 0.0007 | 17.86 | 500 | 0.8974 | 30.4322 | 28.9171 |
 
 
 
 
 
 
 
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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: 0.26380766731643923
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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-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0871
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+ - Wer Ortho: 26.8342
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+ - Wer: 0.2638
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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: 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 Ortho | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
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+ | 0.0021 | 17.86 | 500 | 0.7863 | 26.6304 | 0.2534 |
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+ | 0.0002 | 35.71 | 1000 | 0.8689 | 26.7663 | 0.2612 |
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+ | 0.0001 | 53.57 | 1500 | 0.9230 | 27.2418 | 0.2664 |
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+ | 0.0001 | 71.43 | 2000 | 0.9637 | 27.1739 | 0.2664 |
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+ | 0.0 | 89.29 | 2500 | 0.9977 | 26.9022 | 0.2638 |
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+ | 0.0 | 107.14 | 3000 | 1.0277 | 27.1739 | 0.2664 |
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+ | 0.0 | 125.0 | 3500 | 1.0571 | 27.1739 | 0.2671 |
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+ | 0.0 | 142.86 | 4000 | 1.0871 | 26.8342 | 0.2638 |
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  ### Framework versions
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