metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-gn-hu-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: gn
split: test
args: gn
metrics:
- name: Wer
type: wer
value: 0.5363311494937463
wav2vec2-large-xls-r-300m-gn-hu-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5578
- Wer: 0.5363
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.9484 | 4.97 | 400 | 3.2466 | 1.0 |
| 1.5016 | 9.94 | 800 | 0.6870 | 0.8148 |
| 0.2838 | 14.91 | 1200 | 0.5523 | 0.6087 |
| 0.1566 | 19.88 | 1600 | 0.5592 | 0.5801 |
| 0.105 | 24.84 | 2000 | 0.5685 | 0.5655 |
| 0.0761 | 29.81 | 2400 | 0.5578 | 0.5363 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1