hello_2b

This model is a fine-tuned version of facebook/wav2vec2-xls-r-2b on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

• Loss: 1.2725
• Wer: 0.9531

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: 1e-05
• 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: 500
• num_epochs: 30.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.1646	0.92	100	3.2106	1.0
0.368	1.85	200	2.9963	1.0
0.2252	2.77	300	2.8078	0.9999
0.1546	3.7	400	2.3458	0.9996
0.1468	4.63	500	2.0086	0.9986
0.1261	5.55	600	1.8269	0.9985
0.1206	6.48	700	1.7347	0.9956
0.1959	7.4	800	1.6819	0.9955
0.0502	8.33	900	1.6809	0.9965
0.0811	9.26	1000	1.6674	0.9916
0.0534	10.18	1100	1.5719	0.9898
0.0402	11.11	1200	1.4620	0.9821
0.057	12.04	1300	1.3015	0.9554
0.0385	12.96	1400	1.3798	0.9600
0.0422	13.88	1500	1.3538	0.9699
0.014	14.81	1600	1.2507	0.9443
0.0232	15.74	1700	1.3318	0.9465
0.0554	16.66	1800	1.2784	0.9462
0.0316	17.59	1900	1.2503	0.9481
0.0524	18.51	2000	1.3920	0.9604
0.0142	19.44	2100	1.4224	0.9698
0.0288	20.37	2200	1.3475	0.9635
0.0106	21.29	2300	1.2232	0.9264
0.0396	22.22	2400	1.3323	0.9615
0.0349	23.15	2500	1.2741	0.9587
0.0121	24.07	2600	1.2671	0.9586
0.0224	24.99	2700	1.3001	0.9611
0.0449	25.92	2800	1.2777	0.9572
0.0186	26.85	2900	1.2766	0.9607
0.0365	27.77	3000	1.2935	0.9598
0.0105	28.7	3100	1.2761	0.9588
0.021	29.63	3200	1.2686	0.9528

Framework versions

• Transformers 4.13.0.dev0
• Pytorch 1.10.0
• Datasets 1.15.2.dev0
• Tokenizers 0.10.3