Automatic Speech Recognition
Transformers
PyTorch
Abkhaz
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
# Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("deepdml/output")
model = AutoModelForCTC.from_pretrained("deepdml/output")Quick Links
output
This model is a fine-tuned version of 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: 156.8789
- Wer: 1.3456
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: 10
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="deepdml/output")