Instructions to use Eimhin03/outout_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eimhin03/outout_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Eimhin03/outout_model", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Eimhin03/outout_model") model = AutoModelForSpeechSeq2Seq.from_pretrained("Eimhin03/outout_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
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This model is a fine-tuned version of [Eimhin03/outout_model](https://huggingface.co/Eimhin03/outout_model) on an unknown 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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| Training Loss | Epoch | Step | Validation Loss | Wer |
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### Framework versions
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This model is a fine-tuned version of [Eimhin03/outout_model](https://huggingface.co/Eimhin03/outout_model) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5216
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- Wer: 23.5887
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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| 0.2812 | 0.0248 | 1500 | 0.5216 | 23.5887 |
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### Framework versions
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