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--- |
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language: |
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- en |
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base_model: distil-small.en |
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tags: |
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- generated_from_trainer |
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datasets: |
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- librispeech_asr |
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metrics: |
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- wer |
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model-index: |
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- name: DistilFT-English-10m |
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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: librispeech |
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type: librispeech_asr |
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config: default |
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split: None |
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args: 'config: en, split: test-clean' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 3.5814019853645607 |
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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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# DistilFT-English-10m |
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This model is a fine-tuned version of [distil-small.en](https://huggingface.co/distil-small.en) on the librispeech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5012 |
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- Wer: 3.5814 |
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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: 5e-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 300 |
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- training_steps: 1000 |
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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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| 0.5641 | 33.3333 | 100 | 0.9641 | 3.4754 | |
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| 0.3271 | 66.6667 | 200 | 0.7822 | 3.4652 | |
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| 0.0871 | 100.0 | 300 | 0.5731 | 3.4530 | |
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| 0.0149 | 133.3333 | 400 | 0.5142 | 3.4774 | |
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| 0.0043 | 166.6667 | 500 | 0.5051 | 3.5345 | |
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| 0.0026 | 200.0 | 600 | 0.5030 | 3.5569 | |
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| 0.002 | 233.3333 | 700 | 0.5020 | 3.5671 | |
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| 0.0016 | 266.6667 | 800 | 0.5015 | 3.5773 | |
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| 0.0014 | 300.0 | 900 | 0.5013 | 3.5936 | |
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| 0.0014 | 333.3333 | 1000 | 0.5012 | 3.5814 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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