wav2vec2-large-xls-r-300m-pt-colab

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

• Loss: 0.3637
• Wer: 0.2982

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: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.591	1.15	400	0.9128	0.6517
0.5049	2.31	800	0.4596	0.4437
0.2871	3.46	1200	0.3964	0.3905
0.2077	4.61	1600	0.3958	0.3744
0.1695	5.76	2000	0.4040	0.3720
0.1478	6.92	2400	0.3866	0.3651
0.1282	8.07	2800	0.3987	0.3674
0.1134	9.22	3200	0.4128	0.3688
0.1048	10.37	3600	0.3928	0.3561
0.0938	11.53	4000	0.4048	0.3619
0.0848	12.68	4400	0.4229	0.3555
0.0798	13.83	4800	0.3974	0.3468
0.0688	14.98	5200	0.3870	0.3503
0.0658	16.14	5600	0.3875	0.3351
0.061	17.29	6000	0.4133	0.3417
0.0569	18.44	6400	0.3915	0.3414
0.0526	19.6	6800	0.3957	0.3231
0.0468	20.75	7200	0.4110	0.3301
0.0407	21.9	7600	0.3866	0.3186
0.0384	23.05	8000	0.3976	0.3193
0.0363	24.21	8400	0.3910	0.3177
0.0313	25.36	8800	0.3656	0.3109
0.0293	26.51	9200	0.3712	0.3092
0.0277	27.66	9600	0.3613	0.3054
0.0249	28.82	10000	0.3783	0.3015
0.0234	29.97	10400	0.3637	0.2982

Framework versions

• Transformers 4.11.3
• Pytorch 1.10.0+cu102
• Datasets 1.13.3
• Tokenizers 0.10.3