Wav2Vec2_xls_r_300m_hi_final

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the 'Openslr Multilingual and code-switching ASR challenge' dataset and 'mozilla-foundation/common_voice_7_0' dataset. It achieves the following results on the evaluation set:

• Loss: 0.3035
• Wer: 0.3137
• Cer: 0.0972

  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: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 8
• mixed_precision_training: Native AMP

  Training results

  Training Loss	Epoch	Step	Validation Loss	Wer	Cer
  0.9821	0.64	400	0.5059	0.4783	0.1573
  0.6861	1.28	800	0.4201	0.4247	0.1356
  0.585	1.92	1200	0.3797	0.3811	0.1210
  0.5193	2.56	1600	0.3577	0.3652	0.1152
  0.4583	3.21	2000	0.3422	0.3519	0.1111
  0.4282	3.85	2400	0.3261	0.3450	0.1071
  0.3951	4.49	2800	0.3201	0.3325	0.1048
  0.3619	5.13	3200	0.3167	0.3296	0.1030
  0.345	5.77	3600	0.3157	0.3210	0.1013
  0.338	6.41	4000	0.3051	0.3143	0.0982
  0.3155	7.05	4400	0.3059	0.3154	0.0986
  0.3057	7.69	4800	0.3035	0.3137	0.0972

  Framework versions

• Transformers 4.17.0.dev0
• Pytorch 1.10.2+cu102
• Datasets 1.18.3
• Tokenizers 0.11.0