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
File size: 382 Bytes
dfda964 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"epoch": 0.03,
"eval_loss": 14.213573455810547,
"eval_runtime": 148.129,
"eval_samples": 4620,
"eval_samples_per_second": 31.189,
"eval_steps_per_second": 3.902,
"eval_wer": 1.0,
"train_loss": 12.162414741516113,
"train_runtime": 400.3916,
"train_samples": 11030,
"train_samples_per_second": 0.799,
"train_steps_per_second": 0.025
} |