Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/result_data-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/result_data-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/result_data-4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/result_data-4") model = AutoModelForCTC.from_pretrained("mouseyy/result_data-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 7.0, | |
| "eval_cer": 0.1776461262464016, | |
| "eval_loss": 0.24881185591220856, | |
| "eval_runtime": 16.5577, | |
| "eval_samples": 500, | |
| "eval_samples_per_second": 30.197, | |
| "eval_steps_per_second": 0.966, | |
| "eval_wer": 0.39399943390885933 | |
| } |