wav2vec2-E50_feq_speed3

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

• Loss: 0.9108
• Cer: 19.8766

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
36.8762	0.1289	200	4.9301	100.0
4.9098	0.2579	400	4.6288	100.0
4.7529	0.3868	600	4.6255	100.0
4.7332	0.5158	800	4.6055	100.0
4.6184	0.6447	1000	4.4703	100.0
4.0146	0.7737	1200	3.3130	54.5006
2.9541	0.9026	1400	2.6664	45.6522
2.5007	1.0316	1600	2.2122	38.3431
2.1884	1.1605	1800	1.9481	35.1469
1.9208	1.2895	2000	1.7513	32.5088
1.7158	1.4184	2200	1.7252	32.5617
1.5556	1.5474	2400	1.4556	29.0306
1.4658	1.6763	2600	1.4613	29.5828
1.3603	1.8053	2800	1.2933	26.1281
1.2334	1.9342	3000	1.2106	25.0294
1.1288	2.0632	3200	1.1409	23.7250
1.0335	2.1921	3400	1.0493	22.3854
0.9772	2.3211	3600	1.0525	22.1034
0.9549	2.4500	3800	0.9759	20.9342
0.907	2.5790	4000	0.9405	20.2350
0.8808	2.7079	4200	0.9395	20.2879
0.8458	2.8369	4400	0.9098	19.6886
0.8304	2.9658	4600	0.9108	19.8766

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3