hamidov02's picture
update model card README.md
66afc1b
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-xls-hun-53h-colab
    results: []

wav2vec2-large-xls-hun-53h-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: 0.6027
  • Wer: 0.4618

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: 23
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
13.4225 0.67 100 3.7750 1.0
3.4121 1.34 200 3.3166 1.0
3.2263 2.01 300 3.1403 1.0
3.0038 2.68 400 2.2474 0.9990
1.2243 3.35 500 0.8174 0.7666
0.6368 4.03 600 0.6306 0.6633
0.4426 4.7 700 0.6151 0.6648
0.3821 5.37 800 0.5765 0.6138
0.3337 6.04 900 0.5522 0.5785
0.2832 6.71 1000 0.5822 0.5691
0.2485 7.38 1100 0.5626 0.5449
0.2335 8.05 1200 0.5866 0.5662
0.2031 8.72 1300 0.5574 0.5420
0.1925 9.39 1400 0.5572 0.5297
0.1793 10.07 1500 0.5878 0.5185
0.1652 10.74 1600 0.6173 0.5243
0.1663 11.41 1700 0.5807 0.5133
0.1544 12.08 1800 0.5979 0.5154
0.148 12.75 1900 0.5545 0.4986
0.138 13.42 2000 0.5798 0.4947
0.1353 14.09 2100 0.5670 0.5028
0.1283 14.76 2200 0.5862 0.4957
0.1271 15.43 2300 0.6009 0.4961
0.1108 16.11 2400 0.5873 0.4975
0.1182 16.78 2500 0.6013 0.4893
0.103 17.45 2600 0.6165 0.4898
0.1084 18.12 2700 0.6186 0.4838
0.1014 18.79 2800 0.6122 0.4767
0.1009 19.46 2900 0.5981 0.4793
0.1004 20.13 3000 0.6034 0.4770
0.0922 20.8 3100 0.6127 0.4663
0.09 21.47 3200 0.5967 0.4672
0.0893 22.15 3300 0.6051 0.4611
0.0817 22.82 3400 0.6027 0.4618

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu113
  • Datasets 1.18.3
  • Tokenizers 0.10.3