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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: 12.37 |
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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: 23.62 |
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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: 2.32 |
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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: 180.79 |
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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: 211.01 |
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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: 184.24 |
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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: 48.34 |
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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: 4.81 |
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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: 0.2381 |
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- Wer: 11.1244 |
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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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| 0.3639 | 0.12 | 500 | 0.2512 | 12.9597 | |
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| 0.1931 | 0.25 | 1000 | 0.2123 | 12.1414 | |
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| 0.329 | 1.08 | 1500 | 0.2064 | 11.5818 | |
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| 0.097 | 1.21 | 2000 | 0.2050 | 10.9775 | |
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| 0.0522 | 2.04 | 2500 | 0.2258 | 10.4390 | |
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| 0.1026 | 2.17 | 3000 | 0.2201 | 11.7017 | |
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| 0.0448 | 3.0 | 3500 | 0.2287 | 10.3873 | |
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| 0.0455 | 3.13 | 4000 | 0.2381 | 11.1244 | |
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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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