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--- |
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language: |
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- en |
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license: mit |
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base_model: distil-whisper/distil-small.en |
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tags: |
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- generated_from_trainer |
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datasets: |
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- atc |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large v3 1500 Epochs 2 - nullonesix |
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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: atc |
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type: atc |
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args: 'config: en, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 39.23487544483986 |
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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 Large v3 1500 Epochs 2 - nullonesix |
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This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the atc dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4151 |
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- Wer: 39.2349 |
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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: 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: 500 |
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- training_steps: 1500 |
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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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| 2.8313 | 3.5714 | 100 | 2.7177 | 74.1548 | |
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| 1.1366 | 7.1429 | 200 | 1.6407 | 63.0338 | |
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| 0.4394 | 10.7143 | 300 | 1.4737 | 47.4644 | |
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| 0.1686 | 14.2857 | 400 | 1.4481 | 46.3968 | |
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| 0.0761 | 17.8571 | 500 | 1.3707 | 40.8808 | |
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| 0.0452 | 21.4286 | 600 | 1.4051 | 38.5231 | |
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| 0.0188 | 25.0 | 700 | 1.4044 | 36.7883 | |
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| 0.0167 | 28.5714 | 800 | 1.4217 | 38.8345 | |
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| 0.0084 | 32.1429 | 900 | 1.4120 | 48.5765 | |
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| 0.0033 | 35.7143 | 1000 | 1.4151 | 39.2349 | |
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| 0.0022 | 39.2857 | 1100 | 1.4401 | 39.7242 | |
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| 0.0008 | 42.8571 | 1200 | 1.4591 | 39.5907 | |
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| 0.0007 | 46.4286 | 1300 | 1.4679 | 39.5907 | |
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| 0.0006 | 50.0 | 1400 | 1.4724 | 39.8577 | |
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| 0.0007 | 53.5714 | 1500 | 1.4737 | 39.7242 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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