hello_2b_3 / README.md
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metadata
language:
  - tr
tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: hello_2b_3
    results: []

hello_2b_3

This model is a fine-tuned version of facebook/wav2vec2-xls-r-2b on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5615
  • Wer: 0.9808

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: 5e-06
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.6389 0.92 100 3.6218 1.0
1.6676 1.85 200 3.2655 1.0
0.3067 2.77 300 3.2273 1.0
0.1924 3.7 400 3.0238 0.9999
0.1777 4.63 500 2.1606 0.9991
0.1481 5.55 600 1.8742 0.9982
0.1128 6.48 700 2.0114 0.9994
0.1806 7.4 800 1.9032 0.9984
0.0399 8.33 900 2.0556 0.9996
0.0729 9.26 1000 2.0515 0.9987
0.0847 10.18 1100 2.2121 0.9995
0.0777 11.11 1200 1.7002 0.9923
0.0476 12.04 1300 1.5262 0.9792
0.0518 12.96 1400 1.5990 0.9832
0.071 13.88 1500 1.6326 0.9875
0.0333 14.81 1600 1.5955 0.9870
0.0369 15.74 1700 1.5577 0.9832
0.0689 16.66 1800 1.5415 0.9839
0.0227 17.59 1900 1.5450 0.9878
0.0472 18.51 2000 1.5642 0.9846
0.0214 19.44 2100 1.6103 0.9846
0.0289 20.37 2200 1.6467 0.9898
0.0182 21.29 2300 1.5268 0.9780
0.0439 22.22 2400 1.6001 0.9818
0.06 23.15 2500 1.5481 0.9813
0.0351 24.07 2600 1.5672 0.9820
0.0198 24.99 2700 1.6303 0.9856
0.0328 25.92 2800 1.5958 0.9831
0.0245 26.85 2900 1.5745 0.9809
0.0885 27.77 3000 1.5455 0.9809
0.0224 28.7 3100 1.5378 0.9824
0.0223 29.63 3200 1.5642 0.9810

Framework versions

  • Transformers 4.13.0.dev0
  • Pytorch 1.10.0
  • Datasets 1.15.2.dev0
  • Tokenizers 0.10.3