metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- voxpopuli
metrics:
- wer
model-index:
- name: wav2vec2-classic-300m-norwegian-colab-hung
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: voxpopuli
type: voxpopuli
config: fi
split: test
args: fi
metrics:
- name: Wer
type: wer
value: 1.7882131661442007
wav2vec2-classic-300m-norwegian-colab-hung
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the voxpopuli dataset. It achieves the following results on the evaluation set:
- Loss: 3.8820
- Wer: 1.7882
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.7686 | 2.57 | 400 | 2.9953 | 1.0 |
| 2.5005 | 5.14 | 800 | 2.2739 | 1.9808 |
| 1.6554 | 7.72 | 1200 | 2.4720 | 1.6708 |
| 1.1995 | 10.29 | 1600 | 2.2613 | 1.2480 |
| 0.8972 | 12.86 | 2000 | 2.7599 | 1.8873 |
| 0.6962 | 15.43 | 2400 | 3.2783 | 1.9560 |
| 0.5554 | 18.01 | 2800 | 3.2272 | 1.7544 |
| 0.4234 | 20.58 | 3200 | 3.0755 | 1.5645 |
| 0.3341 | 23.15 | 3600 | 3.5022 | 1.7442 |
| 0.2832 | 25.72 | 4000 | 3.7905 | 1.8324 |
| 0.2293 | 28.3 | 4400 | 3.8820 | 1.7882 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0