End of training
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README.md
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metrics:
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- name: Wer
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type: 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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This model is a fine-tuned version of [deepdml/whisper-large-v3-turbo](https://huggingface.co/deepdml/whisper-large-v3-turbo) on the google/fleurs 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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- Cer: 10.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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### Framework versions
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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## Citation
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Please cite the model using the following BibTeX entry:
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```bibtex
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@misc{deepdml/whisper-large-v3-turbo-ig-mix-norm,
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title={Fine-tuned Whisper turbo ASR model for speech recognition in Lingala},
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author={Jimenez, David},
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howpublished={\url{https://huggingface.co/deepdml/whisper-large-v3-turbo-ig-mix-norm}},
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year={2025}
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}
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```
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metrics:
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- name: Wer
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type: wer
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value: 31.264605428725506
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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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This model is a fine-tuned version of [deepdml/whisper-large-v3-turbo](https://huggingface.co/deepdml/whisper-large-v3-turbo) on the google/fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7028
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- Wer: 31.2646
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- Cer: 10.8084
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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| 0.2019 | 0.2 | 1000 | 0.6438 | 36.4596 | 12.5223 |
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| 0.1293 | 0.4 | 2000 | 0.6558 | 33.7633 | 11.6044 |
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| 0.0589 | 0.6 | 3000 | 0.6882 | 31.8758 | 10.6653 |
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| 0.0504 | 0.8 | 4000 | 0.6845 | 31.0669 | 10.3172 |
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| 0.0353 | 1.0 | 5000 | 0.7028 | 31.2646 | 10.8084 |
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### Framework versions
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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size 3235581408
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