xtreme_s_xlsr_300m_minds14.en-US_2

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.EN-US dataset. It achieves the following results on the evaluation set:

• Loss: 0.5685
• F1: 0.8747
• Accuracy: 0.8759

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: 0.0003
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• total_eval_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 50.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
2.6195	3.95	20	2.6348	0.0172	0.0816
2.5925	7.95	40	2.6119	0.0352	0.0851
2.1271	11.95	60	2.3066	0.1556	0.1986
1.2618	15.95	80	1.3810	0.6877	0.7128
0.5455	19.95	100	1.0403	0.6992	0.7270
0.2571	23.95	120	0.8423	0.8160	0.8121
0.3478	27.95	140	0.6500	0.8516	0.8440
0.0732	31.95	160	0.7066	0.8123	0.8156
0.1092	35.95	180	0.5878	0.8767	0.8759
0.0271	39.95	200	0.5994	0.8578	0.8617
0.4664	43.95	220	0.7830	0.8403	0.8440
0.0192	47.95	240	0.5685	0.8747	0.8759

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1