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---
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license: apache-2.0
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base_model: openai/whisper-tiny.en
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tags:
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- generated_from_trainer
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datasets:
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- tedlium
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metrics:
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- wer
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model-index:
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- name: whisper-tiny-openslrdev
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: tedlium
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type: tedlium
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config: release1
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split: test
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args: release1
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metrics:
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- name: Wer
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type: wer
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value: 90.4153910381297
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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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should probably proofread and complete it, then remove this comment. -->
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# whisper-tiny-openslrdev
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This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the tedlium dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0820
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- Wer: 90.4154
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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: 16
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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: 200
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- training_steps: 300
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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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| No log | 0.06 | 20 | 3.7027 | 35.3291 |
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| 3.9098 | 0.13 | 40 | 3.3264 | 35.0647 |
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| 3.0852 | 0.19 | 60 | 2.9769 | 34.0871 |
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| 2.2682 | 0.26 | 80 | 2.7802 | 31.6309 |
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| 1.6662 | 0.32 | 100 | 2.5284 | 27.7728 |
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| 1.6662 | 0.38 | 120 | 2.4481 | 24.3668 |
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| 1.2505 | 0.45 | 140 | 2.4118 | 21.6532 |
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| 1.0859 | 0.51 | 160 | 2.3687 | 20.9087 |
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| 0.9491 | 0.58 | 180 | 2.1924 | 19.6493 |
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| 0.8746 | 0.64 | 200 | 2.1752 | 22.1229 |
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| 0.8746 | 0.7 | 220 | 2.2546 | 29.7245 |
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| 0.8064 | 0.77 | 240 | 2.1611 | 39.6326 |
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| 0.733 | 0.83 | 260 | 2.1281 | 55.7334 |
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| 0.7135 | 0.89 | 280 | 2.0406 | 75.1705 |
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| 0.6806 | 0.96 | 300 | 2.0820 | 90.4154 |
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### Framework versions
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- Transformers 4.39.2
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- Pytorch 2.2.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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