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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-10h |
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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: 4.4905114250188545 |
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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-10h |
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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: 0.2318 |
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- Wer: 4.4905 |
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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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| 0.651 | 0.5556 | 100 | 0.9641 | 3.4754 | |
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| 0.5006 | 1.1111 | 200 | 0.7651 | 3.5039 | |
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| 0.3531 | 1.6667 | 300 | 0.5188 | 3.5121 | |
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| 0.2176 | 2.2222 | 400 | 0.3514 | 4.0258 | |
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| 0.1834 | 2.7778 | 500 | 0.2878 | 4.3132 | |
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| 0.1587 | 3.3333 | 600 | 0.2589 | 4.4049 | |
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| 0.1553 | 3.8889 | 700 | 0.2447 | 4.5007 | |
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| 0.1566 | 4.4444 | 800 | 0.2370 | 4.5007 | |
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| 0.1226 | 5.0 | 900 | 0.2332 | 4.5048 | |
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| 0.1533 | 5.5556 | 1000 | 0.2318 | 4.4905 | |
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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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