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README.md
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metrics:
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- bleu
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- wer
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model-index:
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- name: Whisper Base GA-EN Speech Translation
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results: []
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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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# Whisper Base GA-EN Speech Translation
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
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- Loss: 1.9005
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- Bleu: 21.83
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- Chrf: 37.13
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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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- Transformers 4.39.3
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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metrics:
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- bleu
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- wer
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- chrf
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model-index:
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- name: Whisper Base GA-EN Speech Translation
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results: []
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datasets:
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- ymoslem/IWSLT2023-GA-EN
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- ymoslem/FLEURS-GA-EN
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language:
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- ga
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- en
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library_name: transformers
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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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# Whisper Base GA-EN Speech Translation
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
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The best model (this version) is at checkpoint 1000, epoch 2.54, and it achieves the following results on the evaluation set:
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- Loss: 1.9005
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- Bleu: 21.83
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- Chrf: 37.13
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## Training procedure
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### Experiment
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- Data (v1.1: IWSLT2023-GA-EN; v1.2: +FLEURS-GA-EN)
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### Training hyperparameters
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The following hyperparameters were used during training:
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- Transformers 4.39.3
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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