wav2vec2-large-xls-r-300m-russian-colab-beam_search_test

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: 0.7619
• Wer: 0.4680

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: 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: 800
• num_epochs: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
10.0158	4.16	100	5.4134	1.0
4.0394	8.33	200	3.4304	1.0
3.2721	12.49	300	3.2273	1.0
3.1277	16.66	400	2.8023	0.9984
1.3791	20.82	500	0.9888	0.8546
0.3659	24.99	600	0.7602	0.6304
0.1858	29.16	700	0.7965	0.6156
0.1403	33.33	800	0.7998	0.5839
0.1173	37.49	900	0.8353	0.5941
0.0917	41.66	1000	0.8272	0.5522
0.0743	45.82	1100	0.8342	0.5471
0.063	49.99	1200	0.7988	0.5352
0.0528	54.16	1300	0.7740	0.5201
0.0456	58.33	1400	0.7636	0.5165
0.0389	62.49	1500	0.7922	0.5161
0.0329	66.66	1600	0.8035	0.5158
0.0283	70.82	1700	0.7873	0.4832
0.0255	74.99	1800	0.7853	0.4870
0.0236	79.16	1900	0.8236	0.5045
0.0202	83.33	2000	0.7661	0.4796
0.0165	87.49	2100	0.7584	0.4680
0.0156	91.66	2200	0.7685	0.4772
0.0149	95.82	2300	0.7519	0.4696
0.0126	99.99	2400	0.7619	0.4680

Framework versions

• Transformers 4.11.3
• Pytorch 1.10.0+cu111
• Datasets 1.18.3
• Tokenizers 0.10.3