wav2vec2-300m-mls-german-ft

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MULTILINGUAL_LIBRISPEECH - GERMAN 10h dataset. It achieves the following results on the evaluation set:

• Loss: 0.2398
• Wer: 0.1520

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 200.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.0132	7.25	500	2.9393	1.0
2.9241	14.49	1000	2.8734	1.0
1.0766	21.74	1500	0.2773	0.2488
0.8416	28.99	2000	0.2224	0.1990
0.8048	36.23	2500	0.2063	0.1792
0.7664	43.48	3000	0.2088	0.1748
0.6571	50.72	3500	0.2042	0.1668
0.7014	57.97	4000	0.2136	0.1649
0.6171	65.22	4500	0.2139	0.1641
0.6609	72.46	5000	0.2144	0.1621
0.6318	79.71	5500	0.2129	0.1600
0.6222	86.96	6000	0.2124	0.1582
0.608	94.2	6500	0.2255	0.1639
0.6099	101.45	7000	0.2265	0.1622
0.6069	108.7	7500	0.2246	0.1593
0.5929	115.94	8000	0.2323	0.1617
0.6218	123.19	8500	0.2287	0.1566
0.5751	130.43	9000	0.2275	0.1563
0.5181	137.68	9500	0.2316	0.1579
0.6306	144.93	10000	0.2372	0.1556
0.5874	152.17	10500	0.2362	0.1533
0.5546	159.42	11000	0.2342	0.1543
0.6294	166.67	11500	0.2381	0.1536
0.5989	173.91	12000	0.2360	0.1527
0.5697	181.16	12500	0.2399	0.1526
0.5379	188.41	13000	0.2375	0.1523
0.5022	195.65	13500	0.2395	0.1519

Framework versions

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