wav2vec2-large-xlsr-53-german-cv9

This model is a fine-tuned version of ./facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - DE dataset.

It achieves the following results on the test set:

  • CER: 2.273015898213336
  • Wer: 9.480663281840769

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Eval Wer
0.4129 1.0 3557 0.3015 0.2499
0.2121 2.0 7114 0.1596 0.1567
0.1455 3.0 10671 0.1377 0.1354
0.1436 4.0 14228 0.1301 0.1282
0.1144 5.0 17785 0.1225 0.1245
0.1219 6.0 21342 0.1254 0.1208
0.104 7.0 24899 0.1198 0.1232
0.1016 8.0 28456 0.1149 0.1174
0.1093 9.0 32013 0.1186 0.1186
0.0858 10.0 35570 0.1182 0.1164
0.102 11.0 39127 0.1191 0.1186
0.0834 12.0 42684 0.1161 0.1096
0.0916 13.0 46241 0.1147 0.1107
0.0811 14.0 49798 0.1174 0.1136
0.0814 15.0 53355 0.1132 0.1114
0.0865 16.0 56912 0.1134 0.1097
0.0701 17.0 60469 0.1096 0.1054
0.0891 18.0 64026 0.1110 0.1076
0.071 19.0 67583 0.1141 0.1074
0.0726 20.0 71140 0.1094 0.1093
0.0647 21.0 74697 0.1088 0.1095
0.0643 22.0 78254 0.1105 0.1044
0.0764 23.0 81811 0.1072 0.1042
0.0605 24.0 85368 0.1095 0.1026
0.0722 25.0 88925 0.1144 0.1066
0.0597 26.0 92482 0.1087 0.1022
0.062 27.0 96039 0.1073 0.1027
0.0536 28.0 99596 0.1068 0.1027
0.0616 29.0 103153 0.1097 0.1037
0.0642 30.0 106710 0.1117 0.1020
0.0555 31.0 110267 0.1109 0.0990
0.0632 32.0 113824 0.1104 0.0977
0.0482 33.0 117381 0.1108 0.0958
0.0601 34.0 120938 0.1095 0.0957
0.0508 35.0 124495 0.1079 0.0973
0.0526 36.0 128052 0.1068 0.0967
0.0487 37.0 131609 0.1081 0.0966
0.0495 38.0 135166 0.1099 0.0956
0.0528 39.0 138723 0.1091 0.0923
0.0439 40.0 142280 0.1111 0.0928
0.0467 41.0 145837 0.1131 0.0943
0.0407 42.0 149394 0.1115 0.0944
0.046 43.0 152951 0.1106 0.0935
0.0447 44.0 156508 0.1083 0.0919
0.0434 45.0 160065 0.1093 0.0909
0.0472 46.0 163622 0.1092 0.0921
0.0414 47.0 167179 0.1106 0.0922
0.0501 48.0 170736 0.1094 0.0918
0.0388 49.0 174293 0.1099 0.0918
0.0428 50.0 177850 0.1103 0.0915

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 2.0.0
  • Tokenizers 0.11.6
Downloads last month
133
Safetensors
Model size
315M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train oliverguhr/wav2vec2-large-xlsr-53-german-cv9

Evaluation results