metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xlsr-turkish-demo-colab
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice
          type: common_voice
          config: tr
          split: test
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 0.4821775099581248

wav2vec2-large-xlsr-turkish-demo-colab

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

Loss: 0.4151
Wer: 0.4822

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
5.2487	4.26	400	1.6455	1.0778
0.71	8.51	800	0.4428	0.6138
0.3073	12.77	1200	0.4214	0.5517
0.2136	17.02	1600	0.4345	0.5193
0.1624	21.28	2000	0.4366	0.5026
0.1298	25.53	2400	0.4111	0.4949
0.1174	29.79	2800	0.4151	0.4822

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2