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chmanoj
/
xls-r-1B-te

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Telugu
wav2vec2
openslr_SLR66
Generated from Trainer
robust-speech-event
hf-asr-leaderboard
Eval Results
Inference Endpoints
Model card Files Metrics Community
1

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the OPENSLR_SLR66 - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3119
  • Wer: 0.2613

Evaluation metrics

Metric Split Decode with LM Value
WER Train No 5.36
CER Train No 1.11
WER Test No 26.14
CER Test No 4.93
WER Train Yes 5.04
CER Train Yes 1.07
WER Test Yes 20.69
CER Test Yes 3.986

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 4
  • 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: 2000
  • num_epochs: 150.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.9038 4.8 500 3.0125 1.0
1.3777 9.61 1000 0.8681 0.8753
1.1436 14.42 1500 0.6256 0.7961
1.0997 19.23 2000 0.5244 0.6875
1.0363 24.04 2500 0.4585 0.6276
0.7996 28.84 3000 0.4072 0.5295
0.825 33.65 3500 0.3590 0.5222
0.8018 38.46 4000 0.3678 0.4671
0.7545 43.27 4500 0.3474 0.3962
0.7375 48.08 5000 0.3224 0.3869
0.6198 52.88 5500 0.3233 0.3630
0.6608 57.69 6000 0.3029 0.3308
0.645 62.5 6500 0.3195 0.3722
0.5249 67.31 7000 0.3004 0.3202
0.4875 72.11 7500 0.2826 0.2992
0.5171 76.92 8000 0.2962 0.2976
0.4974 81.73 8500 0.2990 0.2933
0.4387 86.54 9000 0.2834 0.2755
0.4511 91.34 9500 0.2886 0.2787
0.4112 96.15 10000 0.3093 0.2976
0.4064 100.96 10500 0.3123 0.2863
0.4047 105.77 11000 0.2968 0.2719
0.3519 110.57 11500 0.3106 0.2832
0.3719 115.38 12000 0.3030 0.2737
0.3669 120.19 12500 0.2964 0.2714
0.3386 125.0 13000 0.3101 0.2714
0.3137 129.8 13500 0.3063 0.2710
0.3008 134.61 14000 0.3082 0.2617
0.301 139.42 14500 0.3121 0.2628
0.3291 144.23 15000 0.3105 0.2612
0.3133 149.04 15500 0.3114 0.2624

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0
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Automatic Speech Recognition
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Dataset used to train chmanoj/xls-r-1B-te

Evaluation results

View on Papers With Code