metadata

license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - common_voice_6_1
metrics:
  - wer
model-index:
  - name: wav2vec2-base-turkish-istech
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_6_1
          type: common_voice_6_1
          config: tr
          split: train[:10%]
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 1.0105162523900573

wav2vec2-base-turkish-istech

This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_6_1 dataset. It achieves the following results on the evaluation set:

Loss: 17.9554
Wer: 1.0105

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: 0.0001
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: 20
num_epochs: 0.5
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1