To rerun this experiment, please clone this directory and run:
python create_model.py
followed by
./run_librispeech.sh
wav2vec2-2-bart-large
This model is a fine-tuned version of facebook/wav2vec2-large-lv60 and bart-large on the librispeech_asr - clean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3204
- Wer: 0.0486
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: 4
- eval_batch_size: 4
- gradient_accumulation_steps: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
See Training Metrics Tab.
Framework versions
- Transformers 4.15.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.16.2.dev0
- Tokenizers 0.10.3