hello_2b_3

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: 1.5615
• Wer: 0.9808

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: 5e-06
• 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
3.6389	0.92	100	3.6218	1.0
1.6676	1.85	200	3.2655	1.0
0.3067	2.77	300	3.2273	1.0
0.1924	3.7	400	3.0238	0.9999
0.1777	4.63	500	2.1606	0.9991
0.1481	5.55	600	1.8742	0.9982
0.1128	6.48	700	2.0114	0.9994
0.1806	7.4	800	1.9032	0.9984
0.0399	8.33	900	2.0556	0.9996
0.0729	9.26	1000	2.0515	0.9987
0.0847	10.18	1100	2.2121	0.9995
0.0777	11.11	1200	1.7002	0.9923
0.0476	12.04	1300	1.5262	0.9792
0.0518	12.96	1400	1.5990	0.9832
0.071	13.88	1500	1.6326	0.9875
0.0333	14.81	1600	1.5955	0.9870
0.0369	15.74	1700	1.5577	0.9832
0.0689	16.66	1800	1.5415	0.9839
0.0227	17.59	1900	1.5450	0.9878
0.0472	18.51	2000	1.5642	0.9846
0.0214	19.44	2100	1.6103	0.9846
0.0289	20.37	2200	1.6467	0.9898
0.0182	21.29	2300	1.5268	0.9780
0.0439	22.22	2400	1.6001	0.9818
0.06	23.15	2500	1.5481	0.9813
0.0351	24.07	2600	1.5672	0.9820
0.0198	24.99	2700	1.6303	0.9856
0.0328	25.92	2800	1.5958	0.9831
0.0245	26.85	2900	1.5745	0.9809
0.0885	27.77	3000	1.5455	0.9809
0.0224	28.7	3100	1.5378	0.9824
0.0223	29.63	3200	1.5642	0.9810

Framework versions

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