xls-r-fleurs_nl-run3

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the FLEURS (nl) dataset. It achieves the following results:

• Wer (Validation): 40.48%
• Wer (Test): 40.89%

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0003
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 3
• total_train_batch_size: 12
• 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 (Train)
7.768	0.41	100	3.9649	1.0
3.2646	0.82	200	2.9551	1.0
2.9217	1.23	300	2.9128	1.0
2.9064	1.64	400	2.9067	1.0
2.6775	2.05	500	1.5774	0.9177
1.1026	2.47	600	0.8813	0.7216
0.6905	2.88	700	0.7287	0.6138
0.4936	3.29	800	0.6156	0.5439
0.3837	3.7	900	0.5608	0.4992
0.3176	4.11	1000	0.5326	0.4542
0.2391	4.52	1100	0.5221	0.4466
0.2426	4.93	1200	0.5127	0.4328
0.1882	5.34	1300	0.5311	0.4247
0.1718	5.75	1400	0.5523	0.4266

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3