wav2vec2-large-xls-r-300m-welsh/README.md

language, license, tags, datasets, model-index

language	license	tags	datasets	model-index
cy	apache-2.0	automatic-speech-recognition cy generated_from_trainer hf-asr-leaderboard model_for_talk mozilla-foundation/common_voice_7_0 robust-speech-event	mozilla-foundation/common_voice_7_0	name results XLS-R-300M - Welsh task dataset metrics name type Automatic Speech Recognition automatic-speech-recognition name type args Common Voice 7 mozilla-foundation/common_voice_7_0 cy name type value Test WER wer 31.003 name type value Test CER cer 7.775

wav2vec2-large-xls-r-300m-welsh

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CY dataset. It achieves the following results on the evaluation set:

• Loss: 0.2650
• Wer: 0.2702

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: 7e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 3000
• num_epochs: 50.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3454	8.2	3000	0.4926	0.5703
1.1202	16.39	6000	0.3529	0.3944
1.0058	24.59	9000	0.3143	0.3341
0.9287	32.79	12000	0.2896	0.2980
0.8849	40.98	15000	0.2727	0.2798
0.8665	49.18	18000	0.2662	0.2696

Framework versions

• Transformers 4.16.0.dev0
• Pytorch 1.10.1+cu102
• Datasets 1.18.3
• Tokenizers 0.11.0