metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-sw-ke-tokenizer
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: fleurs
type: fleurs
config: sw_ke
split: test
args: sw_ke
metrics:
- type: wer
value: 0.6223628691983122
name: Wer
wav2vec2-large-xlsr-53-sw-ke-tokenizer
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.9600
- Wer: 0.6224
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.8918 | 4.1667 | 400 | 2.8681 | 1.0 |
| 2.8863 | 8.3333 | 800 | 2.8663 | 1.0 |
| 2.8092 | 12.5 | 1200 | 2.5442 | 1.0 |
| 0.8899 | 16.6667 | 1600 | 0.6992 | 0.6511 |
| 0.2577 | 20.8333 | 2000 | 0.8239 | 0.6385 |
| 0.1397 | 25.0 | 2400 | 0.8893 | 0.6251 |
| 0.0971 | 29.1667 | 2800 | 0.9600 | 0.6224 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2