metadata

language:
  - tr
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: wav2vec2-common_voice-tr-demo
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: COMMON_VOICE - TR
          type: common_voice
          config: tr
          split: test
          args: 'Config: tr, Training split: train+validation, Eval split: test'
        metrics:
          - name: Wer
            type: wer
            value: 0.34950464712491064

wav2vec2-common_voice-tr-demo

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

Loss: 0.3828
Wer: 0.3495

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: 15.0

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.92	100	3.5826	1.0
No log	1.83	200	3.0218	0.9999
No log	2.75	300	0.8985	0.8036
No log	3.67	400	0.5992	0.6197
3.1629	4.59	500	0.4968	0.5340
3.1629	5.5	600	0.4646	0.5045
3.1629	6.42	700	0.4316	0.4425
3.1629	7.34	800	0.4500	0.4735
3.1629	8.26	900	0.4114	0.4123
0.2226	9.17	1000	0.4162	0.4019
0.2226	10.09	1100	0.3999	0.3824
0.2226	11.01	1200	0.4048	0.3842
0.2226	11.93	1300	0.3789	0.3602
0.2226	12.84	1400	0.4024	0.3536
0.1015	13.76	1500	0.3899	0.3575
0.1015	14.68	1600	0.3802	0.3490

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.0
Tokenizers 0.13.3