Automatic Speech Recognition
Transformers
PyTorch
French
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
Eval Results (legacy)
Instructions to use Plim/xls-r-300m-cv_8-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Plim/xls-r-300m-cv_8-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Plim/xls-r-300m-cv_8-fr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Plim/xls-r-300m-cv_8-fr") model = AutoModelForCTC.from_pretrained("Plim/xls-r-300m-cv_8-fr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Get back to checkpoint 17000 and modify readme
Browse files- README.md +5 -16
- pytorch_model.bin +1 -1
README.md
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- automatic-speech-recognition
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model-index:
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- name: ''
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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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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset.
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It achieves the following results on the evaluation set:
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- Loss: inf
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- Wer: 0.9997
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## Model description
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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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## Training procedure
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| 0.8488 | 4.59 | 16000 | inf | 0.2187 |
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| 0.8359 | 4.87 | 17000 | inf | 0.2172 |
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### Framework versions
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- automatic-speech-recognition
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model-index:
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results: []
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---
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## Model description
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset.
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## Training and evaluation data
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It achieves the following results on the evaluation set (Step 17000):
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- Wer: 0.2172
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## Training procedure
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| 0.8488 | 4.59 | 16000 | inf | 0.2187 |
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| 0.8359 | 4.87 | 17000 | inf | 0.2172 |
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Got some issue with validation loss calculation.
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### Framework versions
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pytorch_model.bin
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