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---
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library_name: transformers
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license: apache-2.0
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base_model: openai/whisper-tiny
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tags:
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- generated_from_trainer
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datasets:
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- audiofolder
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metrics:
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- wer
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model-index:
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- name: whisper-tiny-as-LDCIL-sentenceAligned_ChotaTesting
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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: audiofolder
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type: audiofolder
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config: default
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split: train
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 125.97765363128492
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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-as-LDCIL-sentenceAligned_ChotaTesting
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3640
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- Wer: 125.9777
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: constant_with_warmup
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- lr_scheduler_warmup_steps: 20
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- training_steps: 100
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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 | 0.4 | 20 | 1.8993 | 156.5992 |
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| 2.2744 | 0.8 | 40 | 1.5240 | 183.4846 |
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| 1.5738 | 1.2 | 60 | 1.4388 | 129.3296 |
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| 1.432 | 1.6 | 80 | 1.3968 | 137.8142 |
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| 1.364 | 2.0 | 100 | 1.3640 | 125.9777 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.4.0+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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