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Leotrim
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whisper-tiny-en

Automatic Speech Recognition
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Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
 Metrics Community
Leotrim commited on
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End of training

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  1. README.md +10 -11
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,8 +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: 35.89887640449439
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- pipeline_tag: automatic-speech-recognition
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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
@@ -33,9 +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: 3.4448
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- - Wer Ortho: 48.1176
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- - Wer: 35.8989
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  ## Model description
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@@ -63,15 +62,15 @@ 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: 2
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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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- | 3.7692 | 0.0714 | 1 | 3.4448 | 48.1176 | 35.8989 |
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- | 3.3965 | 0.1429 | 2 | 3.4448 | 48.1176 | 35.8989 |
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  ### Framework versions
@@ -79,4 +78,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.42.3
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  - Pytorch 2.1.2
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  - Datasets 2.20.0
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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: 0.28903857930189836
 
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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: 0.5945
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+ - Wer Ortho: 0.2898
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+ - Wer: 0.2890
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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: 200
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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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+ | 0.2419 | 7.1429 | 100 | 0.4865 | 0.2942 | 0.2866 |
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+ | 0.0048 | 14.2857 | 200 | 0.5945 | 0.2898 | 0.2890 |
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  ### Framework versions
 
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  - Transformers 4.42.3
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  - Pytorch 2.1.2
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  - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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