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--- |
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library_name: transformers |
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language: |
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- en |
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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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- wft |
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- whisper |
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- automatic-speech-recognition |
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- audio |
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- speech |
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- generated_from_trainer |
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datasets: |
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- hf-internal-testing/librispeech_asr_dummy |
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metrics: |
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- wer |
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model-index: |
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- name: wft-test-model |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: hf-internal-testing/librispeech_asr_dummy |
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type: hf-internal-testing/librispeech_asr_dummy |
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metrics: |
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- type: wer |
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value: 4.724409448818897 |
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name: Wer |
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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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# wft-test-model |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the hf-internal-testing/librispeech_asr_dummy dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1248 |
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- Wer: 4.7244 |
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- Cer: 92.6847 |
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- Decode Time: 0.5481 |
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- Wer Time: 0.0069 |
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- Cer Time: 0.0040 |
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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: 0.0005 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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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: 50 |
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- training_steps: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Time | Wer Time | Cer Time | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:--------:|:--------:| |
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| 2.4107 | 0.1 | 10 | 1.9892 | 303.5433 | 117.1875 | 0.5449 | 0.0307 | 0.0039 | |
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| 1.2109 | 1.01 | 20 | 1.1659 | 155.1181 | 91.2642 | 0.5278 | 0.0062 | 0.0036 | |
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| 0.8855 | 1.11 | 30 | 0.8104 | 30.7087 | 56.8182 | 0.4832 | 0.0069 | 0.0041 | |
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| 0.4367 | 2.02 | 40 | 0.6315 | 25.1969 | 74.5739 | 0.5295 | 0.0058 | 0.0034 | |
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| 0.4398 | 2.12 | 50 | 0.4566 | 17.3228 | 91.9744 | 0.6078 | 0.0055 | 0.0030 | |
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| 0.2291 | 3.03 | 60 | 0.3006 | 9.0551 | 100.7102 | 0.5659 | 0.0058 | 0.0031 | |
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| 0.2281 | 3.13 | 70 | 0.2144 | 7.4803 | 90.4830 | 0.5507 | 0.0046 | 0.0030 | |
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| 0.111 | 4.04 | 80 | 0.1736 | 5.9055 | 89.3466 | 0.6595 | 0.0063 | 0.0032 | |
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| 0.0695 | 4.14 | 90 | 0.1345 | 4.7244 | 87.9261 | 0.6369 | 0.0402 | 0.0182 | |
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| 0.0761 | 5.05 | 100 | 0.1248 | 4.7244 | 92.6847 | 0.5481 | 0.0069 | 0.0040 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.45.2 |
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- Pytorch 2.5.0 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
