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--- |
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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-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- edinburghcstr/ami |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small - FutureProofGlitch |
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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: AMI Meeting Corpus |
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type: edinburghcstr/ami |
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config: ihm |
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split: test |
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args: ihm |
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metrics: |
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- name: Wer |
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type: wer |
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value: 19.383175582260982 |
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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 Small - FutureProofGlitch |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AMI Meeting Corpus dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4325 |
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- Wer Ortho: 19.5838 |
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- Wer: 19.3832 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 4000 |
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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 Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| |
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| 0.2735 | 0.61 | 500 | 0.3324 | 21.5310 | 21.2081 | |
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| 0.1235 | 1.22 | 1000 | 0.3473 | 19.6819 | 19.4991 | |
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| 0.1317 | 1.83 | 1500 | 0.3342 | 19.0920 | 18.7929 | |
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| 0.0647 | 2.44 | 2000 | 0.3671 | 22.8615 | 22.6949 | |
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| 0.0294 | 3.05 | 2500 | 0.3842 | 18.5566 | 18.4101 | |
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| 0.0534 | 3.66 | 3000 | 0.4044 | 20.8094 | 20.5998 | |
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| 0.0366 | 4.27 | 3500 | 0.4277 | 20.2686 | 20.1372 | |
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| 0.0328 | 4.88 | 4000 | 0.4325 | 19.5838 | 19.3832 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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