iloko_model

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0095
• Wer: 0.0840

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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.2784	1.11	100	2.9875	1.0
2.6899	2.22	200	2.6741	1.0
2.6177	3.33	300	2.6516	1.0
2.5327	4.44	400	2.4530	1.0
0.8653	5.56	500	0.5227	0.6547
0.3414	6.67	600	0.1830	0.2487
0.2299	7.78	700	0.1212	0.1877
0.1739	8.89	800	0.0843	0.1441
0.1242	10.0	900	0.0766	0.1441
0.1116	11.11	1000	0.0530	0.1145
0.0861	12.22	1100	0.0442	0.1047
0.1007	13.33	1200	0.0379	0.1023
0.0613	14.44	1300	0.0291	0.1006
0.0629	15.56	1400	0.0264	0.0961
0.047	16.67	1500	0.0238	0.0935
0.0797	17.78	1600	0.0226	0.0913
0.034	18.89	1700	0.0197	0.0893
0.0485	20.0	1800	0.0173	0.0905
0.0402	21.11	1900	0.0148	0.0902
0.0231	22.22	2000	0.0135	0.0891
0.0512	23.33	2100	0.0134	0.0861
0.0181	24.44	2200	0.0118	0.0842
0.0371	25.56	2300	0.0116	0.0867
0.0342	26.67	2400	0.0104	0.0863
0.0344	27.78	2500	0.0100	0.0850
0.0182	28.89	2600	0.0096	0.0839
0.0171	30.0	2700	0.0095	0.0840

Framework versions

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