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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: openai/whisper-large-v2 |
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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: rishabhjain16/infer_myst |
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type: rishabhjain16/infer_myst |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 11.73 |
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name: WER |
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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: rishabhjain16/infer_pfs |
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type: rishabhjain16/infer_pfs |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 3.13 |
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name: WER |
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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: rishabhjain16/infer_cmu |
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type: rishabhjain16/infer_cmu |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 2.56 |
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name: WER |
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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: rishabhjain16/libritts_dev_clean |
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type: rishabhjain16/libritts_dev_clean |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 4.69 |
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name: WER |
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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: rishabhjain16/infer_pf_swedish |
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type: rishabhjain16/infer_pf_swedish |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 9.67 |
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name: WER |
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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: rishabhjain16/infer_pf_german |
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type: rishabhjain16/infer_pf_german |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 35.05 |
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name: WER |
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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: rishabhjain16/infer_pf_italian |
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type: rishabhjain16/infer_pf_italian |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 5.51 |
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name: WER |
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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: rishabhjain16/infer_so_chinese |
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type: rishabhjain16/infer_so_chinese |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 15.83 |
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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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# openai/whisper-large-v2 |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1915 |
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- Wer: 10.0336 |
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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: 32 |
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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: 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.2819 | 0.12 | 500 | 0.2709 | 15.1530 | |
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| 0.2508 | 0.25 | 1000 | 0.2098 | 11.2876 | |
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| 0.1113 | 1.01 | 1500 | 0.2127 | 10.3778 | |
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| 0.2872 | 1.14 | 2000 | 0.1891 | 10.6509 | |
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| 0.2995 | 1.26 | 2500 | 0.1883 | 10.7545 | |
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| 0.0701 | 2.02 | 3000 | 0.1972 | 9.6061 | |
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| 0.0613 | 2.15 | 3500 | 0.2073 | 9.4813 | |
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| 0.1135 | 2.27 | 4000 | 0.1915 | 10.0336 | |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.9.1.dev0 |
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- Tokenizers 0.13.2 |
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