wav2vec2-Y_speed_pause

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: 4.3872
• Cer: 84.5042

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• 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
34.8148	0.1289	200	5.1751	100.0
5.0795	0.2579	400	4.7170	100.0
4.8952	0.3868	600	4.8290	100.0
4.8428	0.5158	800	4.6400	100.0
4.7434	0.6447	1000	4.8620	100.0
4.7062	0.7737	1200	4.7443	97.9500
4.6626	0.9026	1400	4.8160	98.8898
4.5942	1.0316	1600	4.6878	93.9145
4.5619	1.1605	1800	5.0049	95.1598
4.512	1.2895	2000	4.9230	93.9380
4.4579	1.4184	2200	5.0219	94.1377
4.4503	1.5474	2400	4.5823	89.5383
4.35	1.6763	2600	4.6256	91.7704
4.3369	1.8053	2800	4.5154	93.3858
4.2476	1.9342	3000	4.4953	89.7968
4.1991	2.0632	3200	4.4719	83.4234
4.1593	2.1921	3400	4.4864	91.2359
4.0994	2.3211	3600	4.3783	89.6264
4.0728	2.4500	3800	4.4647	87.2122
4.0264	2.5790	4000	4.4085	87.1182
3.9909	2.7079	4200	4.3572	85.7025
3.9374	2.8369	4400	4.3802	84.3574
3.9498	2.9658	4600	4.3872	84.5042

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1