README.md

metadata

language:
  - tr
license: apache-2.0
tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  - tr
  - robust-speech-event
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: wav2vec2-base-turkish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 6.1
          type: common_voice
          args: tr
        metrics:
          - name: Test WER
            type: wer
            value: 9.437
          - name: Test CER
            type: cer
            value: 3.325
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: tr
        metrics:
          - name: Test WER
            type: wer
            value: 8.147
          - name: Test CER
            type: cer
            value: 2.802
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 8
          type: mozilla-foundation/common_voice_8_0
          args: tr
        metrics:
          - name: Test WER
            type: wer
            value: 8.335
          - name: Test CER
            type: cer
            value: 2.336
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: tr
        metrics:
          - name: Test WER
            type: wer
            value: 28.011
          - name: Test CER
            type: cer
            value: 10.66

This model is a fine-tuned version of cahya/wav2vec2-base-turkish-artificial-cv on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

• Loss: 0.1337
• Wer: 0.1353

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

The following datasets were used for finetuning:

• Common Voice 7.0 TR 'train', 'validation' and 'other' split were used for training.
• Media Speech
• Magic Hub

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 7.5e-06
• train_batch_size: 6
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 24
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2000
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.1224	3.45	500	0.1641	0.1396

Framework versions

• Transformers 4.17.0.dev0
• Pytorch 1.10.1+cu102
• Datasets 1.18.2
• Tokenizers 0.10.3