metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: Check_Model_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: 0.2728883087823979
Check_Model_2
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: 0.3499
- Wer: 0.2729
- Cer: 0.0673
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 |
|---|---|---|---|---|---|
| 3.8708 | 3.23 | 400 | 0.7345 | 0.7259 | 0.2034 |
| 0.4247 | 6.45 | 800 | 0.4128 | 0.4268 | 0.1102 |
| 0.2047 | 9.68 | 1200 | 0.3726 | 0.3795 | 0.0930 |
| 0.1422 | 12.9 | 1600 | 0.3690 | 0.3514 | 0.0884 |
| 0.1139 | 16.13 | 2000 | 0.3811 | 0.3160 | 0.0794 |
| 0.089 | 19.35 | 2400 | 0.3650 | 0.2895 | 0.0731 |
| 0.0709 | 22.58 | 2800 | 0.3629 | 0.2944 | 0.0727 |
| 0.0594 | 25.81 | 3200 | 0.3538 | 0.2779 | 0.0692 |
| 0.0478 | 29.03 | 3600 | 0.3499 | 0.2729 | 0.0673 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 1.18.3
- Tokenizers 0.13.3