metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-dv
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: dv
split: test
args: dv
metrics:
- name: Wer
type: wer
value: 0.5420287839810888
wav2vec2-large-xls-r-300m-dv
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4688
- Wer: 0.5420
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
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.7748 | 2.5993 | 400 | 0.9977 | 0.8406 |
| 0.5528 | 5.1954 | 800 | 0.5006 | 0.6392 |
| 0.2781 | 7.7948 | 1200 | 0.4461 | 0.5797 |
| 0.1713 | 10.3909 | 1600 | 0.4591 | 0.5631 |
| 0.118 | 12.9902 | 2000 | 0.4688 | 0.5420 |
Framework versions
- Transformers 4.55.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4