Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Kasem
wav2vec2
Generated from Trainer
Instructions to use ghananlpcommunity/w2v2-lg-xls-r-300m-kasem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghananlpcommunity/w2v2-lg-xls-r-300m-kasem with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ghananlpcommunity/w2v2-lg-xls-r-300m-kasem")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ghananlpcommunity/w2v2-lg-xls-r-300m-kasem") model = AutoModelForCTC.from_pretrained("ghananlpcommunity/w2v2-lg-xls-r-300m-kasem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
w2v2-lg-xls-r-300m-kasem
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m.
It achieves the following results on the evaluation set:
- eval_loss: 1.99408
- eval_wer: 0.30174
- eval_runtime: 308.9313
- eval_samples_per_second: 11.252
- eval_steps_per_second: 1.408
- epoch: 28.8434
- step: 57600
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Model tree for ghananlpcommunity/w2v2-lg-xls-r-300m-kasem
Base model
facebook/wav2vec2-xls-r-300m