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	---
	language:
	- de
	license: apache-2.0
	tags:
	- automatic-speech-recognition
	- mozilla-foundation/common_voice_9_0
	- generated_from_trainer
	datasets:
	- mozilla-foundation/common_voice_9_0
	model-index:
	- name: wav2vec2-large-xlsr-53-german-cv9
	results:
	- task:
	name: Automatic Speech Recognition
	type: automatic-speech-recognition
	dataset:
	name: Common Voice 9
	type: mozilla-foundation/common_voice_9_0
	args: de
	metrics:
	- name: Test WER
	type: wer
	value: 9.480663281840769
	- name: Test CER
	type: cer
	value: 1.9167347943074394
	- task:
	name: Automatic Speech Recognition
	type: automatic-speech-recognition
	dataset:
	name: Common Voice 9
	type: mozilla-foundation/common_voice_9_0
	args: de
	metrics:
	- name: Test WER (+LM)
	type: wer
	value: 7.49027762774117
	- name: Test CER (+LM)
	type: cer
	value: 1.9167347943074394
	- task:
	name: Automatic Speech Recognition
	type: automatic-speech-recognition
	dataset:
	name: Common Voice 6.1
	type: common_voice
	args: de
	metrics:
	- name: Test WER
	type: wer
	value: 8.122005951166668
	- name: Test CER
	type: cer
	value: 1.
	- task:
	name: Automatic Speech Recognition
	type: automatic-speech-recognition
	dataset:
	name: Common Voice 6.1
	type: common_voice
	args: de
	metrics:
	- name: Test WER (+LM)
	type: wer
	value: 6.1453182045203544
	- name: Test CER (+LM)
	type: cer
	value: 1.5247743373447677
	---

	# wav2vec2-large-xlsr-53-german-cv9

	This model is a fine-tuned version of [./facebook/wav2vec2-large-xlsr-53](https://huggingface.co/./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