metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-demo-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: sah
split: test
args: sah
metrics:
- name: Wer
type: wer
value: 0.5698038864511508
wav2vec2-large-xlsr-53-demo-colab
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8836
- Wer: 0.5698
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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1354 | 14.04 | 400 | 0.8703 | 0.6377 |
| 0.1297 | 28.07 | 800 | 0.8601 | 0.6317 |
| 0.0937 | 42.11 | 1200 | 0.9103 | 0.6320 |
| 0.0751 | 56.14 | 1600 | 0.8848 | 0.6044 |
| 0.0582 | 70.18 | 2000 | 0.8630 | 0.5770 |
| 0.0492 | 84.21 | 2400 | 0.8889 | 0.5786 |
| 0.0402 | 98.25 | 2800 | 0.8836 | 0.5698 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1