wav2vec2-E10_speed_

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: 1.6602
• Cer: 34.2516

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
44.1964	0.1289	200	5.2076	100.0
5.045	0.2579	400	4.6479	100.0
4.8481	0.3868	600	4.6312	100.0
4.826	0.5158	800	4.6426	100.0
4.7515	0.6447	1000	4.6169	100.0
4.7334	0.7737	1200	4.5910	100.0
4.7044	0.9026	1400	4.6351	99.3539
4.6229	1.0316	1600	4.4962	98.3376
4.4894	1.1605	1800	4.3968	98.7723
3.9914	1.2895	2000	3.7402	68.3564
3.3225	1.4184	2200	3.0907	60.9199
2.8339	1.5474	2400	2.8334	55.0869
2.5629	1.6763	2600	2.5656	51.3099
2.3462	1.8053	2800	2.3671	47.7914
2.1493	1.9342	3000	2.2319	45.6473
1.9705	2.0632	3200	2.0758	42.4048
1.7687	2.1921	3400	1.9741	41.0244
1.6915	2.3211	3600	1.8859	39.4267
1.6005	2.4500	3800	1.8049	37.2180
1.5535	2.5790	4000	1.6690	34.2634
1.5046	2.7079	4200	1.7165	35.4852
1.4463	2.8369	4400	1.6631	34.6217
1.4025	2.9658	4600	1.6602	34.2516

Framework versions

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