Automatic Speech Recognition
Transformers
PyTorch
Abkhaz
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
Instructions to use deepdml/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepdml/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="deepdml/output")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("deepdml/output") model = AutoModelForCTC.from_pretrained("deepdml/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.028409090909090908, | |
| "global_step": 10, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.03, | |
| "step": 10, | |
| "total_flos": 508182128640.0, | |
| "train_loss": 94.46571044921875, | |
| "train_runtime": 11.7935, | |
| "train_samples_per_second": 1.696, | |
| "train_steps_per_second": 0.848 | |
| } | |
| ], | |
| "max_steps": 10, | |
| "num_train_epochs": 1, | |
| "total_flos": 508182128640.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |