metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: Model_G_2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: id
split: test
args: id
metrics:
- name: Wer
type: wer
value: 0.251258623904531
Model_G_2
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3710
- Wer: 0.2513
- Cer: 0.0631
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 | Cer |
|---|---|---|---|---|---|
| 3.7484 | 3.23 | 400 | 0.5706 | 0.5698 | 0.1477 |
| 0.3419 | 6.45 | 800 | 0.4120 | 0.3758 | 0.0924 |
| 0.1796 | 9.68 | 1200 | 0.3691 | 0.3295 | 0.0843 |
| 0.125 | 12.9 | 1600 | 0.3821 | 0.3097 | 0.0782 |
| 0.0984 | 16.13 | 2000 | 0.4085 | 0.2947 | 0.0742 |
| 0.0827 | 19.35 | 2400 | 0.3859 | 0.2781 | 0.0711 |
| 0.0666 | 22.58 | 2800 | 0.3813 | 0.2663 | 0.0684 |
| 0.0558 | 25.81 | 3200 | 0.3681 | 0.2545 | 0.0644 |
| 0.0466 | 29.03 | 3600 | 0.3710 | 0.2513 | 0.0631 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 1.18.3
- Tokenizers 0.13.3