metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - openslr
metrics:
  - wer
model-index:
  - name: wav2vec2-telugu
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: openslr
          type: openslr
          config: SLR66
          split: train
          args: SLR66
        metrics:
          - name: Wer
            type: wer
            value: 0.2884547694473777

wav2vec2-telugu

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the openslr dataset. It achieves the following results on the evaluation set:

Loss: 0.2982
Wer: 0.2885

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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
6.6905	3.84	400	0.7109	0.7800
0.4532	7.69	800	0.2972	0.3977
0.1957	11.54	1200	0.2907	0.3522
0.1284	15.38	1600	0.3117	0.3317
0.0979	19.23	2000	0.3000	0.3353
0.0749	23.08	2400	0.2823	0.3045
0.0584	26.92	2800	0.2982	0.2885

Framework versions

Transformers 4.24.0
Pytorch 1.13.0+cu117
Datasets 2.6.1
Tokenizers 0.13.2