metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-04
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: tw
split: test
args: tw
metrics:
- name: Wer
type: wer
value: 0.625
wav2vec2-large-xlsr-53-AsanteTwi-04
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: 0.7250
- Wer: 0.625
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: 100
- num_epochs: 90
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 13.2642 | 8.33 | 50 | 4.7327 | 1.0 |
| 3.1075 | 16.67 | 100 | 3.1680 | 1.0 |
| 2.8849 | 25.0 | 150 | 2.9745 | 1.0 |
| 2.8553 | 33.33 | 200 | 2.9167 | 1.0 |
| 2.8333 | 41.67 | 250 | 2.8538 | 1.0 |
| 2.6501 | 50.0 | 300 | 2.3417 | 1.0 |
| 1.8966 | 58.33 | 350 | 1.1529 | 0.875 |
| 0.9431 | 66.67 | 400 | 0.8519 | 0.75 |
| 0.5951 | 75.0 | 450 | 0.7970 | 0.625 |
| 0.444 | 83.33 | 500 | 0.7250 | 0.625 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3