metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-jana-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: cy
split: test
args: cy
metrics:
- name: Wer
type: wer
value: 0.6497412901000345
wav2vec2-large-xls-r-300m-jana-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.8913
- Wer: 0.6497
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.6444 | 1.67 | 200 | 2.9379 | 1.0 |
| 2.7964 | 3.33 | 400 | 1.9912 | 0.9927 |
| 1.1945 | 5.0 | 600 | 0.9492 | 0.7889 |
| 0.6065 | 6.67 | 800 | 0.8534 | 0.7137 |
| 0.3859 | 8.33 | 1000 | 0.8933 | 0.6689 |
| 0.2724 | 10.0 | 1200 | 0.8913 | 0.6497 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3