wav2vec2-E10_freq_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: 1.2920
• Cer: 28.2366

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
28.8751	0.1289	200	4.9115	100.0
5.0006	0.2579	400	4.7238	100.0
4.8671	0.3868	600	4.6553	100.0
4.823	0.5158	800	4.6273	100.0
4.7298	0.6447	1000	4.6856	100.0
4.6744	0.7737	1200	4.5653	99.2540
4.4414	0.9026	1400	4.3734	98.8781
3.5827	1.0316	1600	3.2674	59.4514
2.7774	1.1605	1800	2.6359	52.0089
2.3795	1.2895	2000	2.3016	43.4152
2.1081	1.4184	2200	2.0953	40.3783
1.9172	1.5474	2400	1.9540	37.8642
1.7123	1.6763	2600	1.7923	35.4382
1.5885	1.8053	2800	1.7213	35.2796
1.4393	1.9342	3000	1.5884	32.5247
1.3138	2.0632	3200	1.5391	32.6598
1.2288	2.1921	3400	1.4909	31.2794
1.1505	2.3211	3600	1.4126	30.3160
1.1316	2.4500	3800	1.4099	30.6743
1.0684	2.5790	4000	1.3603	28.8769
1.0779	2.7079	4200	1.3231	28.1896
1.0489	2.8369	4400	1.3002	28.3306
1.0278	2.9658	4600	1.2920	28.2366

Framework versions

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