End of training
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- adapter_model.safetensors +1 -1
README.md
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metrics:
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- wer
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model-index:
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- name: SPEAK-ASR/whisper-si-exp-
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results:
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- task:
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type: automatic-speech-recognition
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args: 'config: si, split: test'
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metrics:
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- type: wer
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value:
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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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# SPEAK-ASR/whisper-si-exp-
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SPEAK-ASR/openslr-sinhala-asr-preprocessed-1 | SPEAK-ASR/openslr-sinhala-asr-preprocessed-2 | SPEAK-ASR/openslr-sinhala-asr-preprocessed-3 | SPEAK-ASR/youtube-sinhala-asr-preprocessed dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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## Model description
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs:
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### Training results
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| 0.6370 | 11.4796 | 13500 | 0.1652 | 21.7635 |
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| 0.6355 | 12.7551 | 15000 | 0.1632 | 21.4154 |
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| 0.6367 | 14.0306 | 16500 | 0.1620 | 21.2375 |
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### Framework versions
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metrics:
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- wer
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model-index:
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- name: SPEAK-ASR/whisper-si-exp-7
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results:
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- task:
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type: automatic-speech-recognition
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args: 'config: si, split: test'
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metrics:
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- type: wer
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value: 20.728200160443187
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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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# SPEAK-ASR/whisper-si-exp-7
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SPEAK-ASR/openslr-sinhala-asr-preprocessed-1 | SPEAK-ASR/openslr-sinhala-asr-preprocessed-2 | SPEAK-ASR/openslr-sinhala-asr-preprocessed-3 | SPEAK-ASR/youtube-sinhala-asr-preprocessed dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1581
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- Wer: 20.7282
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## Model description
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 20.0
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### Training results
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| 0.6370 | 11.4796 | 13500 | 0.1652 | 21.7635 |
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| 0.6355 | 12.7551 | 15000 | 0.1632 | 21.4154 |
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| 0.6367 | 14.0306 | 16500 | 0.1620 | 21.2375 |
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| 0.6320 | 15.3061 | 18000 | 0.1622 | 21.2300 |
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| 0.6196 | 16.5816 | 19500 | 0.1600 | 21.0468 |
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| 0.6069 | 17.8571 | 21000 | 0.1590 | 20.8690 |
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| 0.6063 | 19.1327 | 22500 | 0.1581 | 20.7282 |
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### Framework versions
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adapter_model.safetensors
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