# Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("golesheed/wav2vec2-large-xls-r-1b-frisian-cv-13-elderly-augmented")
model = AutoModelForCTC.from_pretrained("golesheed/wav2vec2-large-xls-r-1b-frisian-cv-13-elderly-augmented", device_map="auto")Quick Links
wav2vec2-large-xls-r-1b-frisian-cv-13-elderly-augmented
This model is a fine-tuned version of greenw0lf/wav2vec2-large-xls-r-1b-frisian on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2158
- Wer: 0.2709
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: 9e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.7704 | 2.5 | 50 | 3.5242 | 1.0040 |
| 2.7638 | 5.0 | 100 | 1.8583 | 1.0523 |
| 1.4635 | 7.5 | 150 | 0.5541 | 0.5861 |
| 0.6753 | 10.0 | 200 | 0.2995 | 0.3353 |
| 0.4331 | 12.5 | 250 | 0.2439 | 0.2964 |
| 0.7712 | 15.0 | 300 | 0.2344 | 0.2879 |
| 0.6968 | 17.5 | 350 | 0.2287 | 0.2839 |
| 0.2765 | 20.0 | 400 | 0.2249 | 0.2776 |
| 0.4245 | 22.5 | 450 | 0.2202 | 0.2776 |
| 0.3709 | 25.0 | 500 | 0.2192 | 0.2754 |
| 0.4728 | 27.5 | 550 | 0.2195 | 0.2763 |
| 0.6297 | 30.0 | 600 | 0.2191 | 0.2736 |
| 0.5297 | 32.5 | 650 | 0.2186 | 0.2758 |
| 0.3543 | 35.0 | 700 | 0.2171 | 0.2731 |
| 0.2973 | 37.5 | 750 | 0.2167 | 0.2713 |
| 0.4558 | 40.0 | 800 | 0.2158 | 0.2709 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="golesheed/wav2vec2-large-xls-r-1b-frisian-cv-13-elderly-augmented")