Automatic Speech Recognition
Transformers
PyTorch
Swedish
wav2vec2
mozilla-foundation/common_voice_9_0
Generated from Trainer
Eval Results (legacy)
Instructions to use marinone94/xls-r-300m-sv-robust with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marinone94/xls-r-300m-sv-robust with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="marinone94/xls-r-300m-sv-robust")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("marinone94/xls-r-300m-sv-robust") model = AutoModelForCTC.from_pretrained("marinone94/xls-r-300m-sv-robust") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 8421a48
update model card README.md
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README.md
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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_7_0 - SV-SE dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Wer: 1.0
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## Model description
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps:
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- num_epochs:
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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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_7_0 - SV-SE dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.9141
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- Wer: 1.0
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## Model description
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 20
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- num_epochs: 2.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:---:|
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| 2.9357 | 1.45 | 500 | 2.9459 | 1.0 |
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### Framework versions
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