Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Abkhaz
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_7_0
robust-speech-event
Instructions to use cahya/xls-r-ab-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/xls-r-ab-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cahya/xls-r-ab-test")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("cahya/xls-r-ab-test") model = AutoModelForCTC.from_pretrained("cahya/xls-r-ab-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - ab | |
| tags: | |
| - ab | |
| - automatic-speech-recognition | |
| - generated_from_trainer | |
| - hf-asr-leaderboard | |
| - mozilla-foundation/common_voice_7_0 | |
| - robust-speech-event | |
| datasets: | |
| - mozilla-foundation/common_voice_7_0 | |
| model-index: | |
| - name: '' | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # | |
| This model is a fine-tuned version of [hf-test/xls-r-dummy](https://huggingface.co/hf-test/xls-r-dummy) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AB dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 135.4675 | |
| - Wer: 1.0 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.0003 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - training_steps: 100 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.17.0.dev0 | |
| - Pytorch 1.10.1+cu102 | |
| - Datasets 1.18.2.dev0 | |
| - Tokenizers 0.10.3 | |