wav2vec2-E10_speed2_

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: 1.8373
• Cer: 35.0353

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
44.0517	0.1289	200	5.2881	100.0
5.0678	0.2579	400	4.6640	100.0
4.8617	0.3868	600	4.6368	100.0
4.8476	0.5158	800	4.6517	100.0
4.7683	0.6447	1000	4.6522	100.0
4.7437	0.7737	1200	4.5665	100.0
4.7147	0.9026	1400	4.6060	100.0
4.6579	1.0316	1600	4.5314	100.0
4.6231	1.1605	1800	4.6514	99.9471
4.4643	1.2895	2000	4.3773	98.1727
4.292	1.4184	2200	4.2086	92.5734
3.8631	1.5474	2400	3.7279	67.4266
3.3619	1.6763	2600	3.1229	57.7380
2.9826	1.8053	2800	2.9814	55.7403
2.7082	1.9342	3000	2.7001	50.0353
2.4949	2.0632	3200	2.4357	44.9295
2.2833	2.1921	3400	2.2863	43.0846
2.141	2.3211	3600	2.1369	39.6769
2.0008	2.4500	3800	2.0446	38.5840
1.9496	2.5790	4000	1.9128	36.3220
1.8774	2.7079	4200	1.8870	35.8108
1.7961	2.8369	4400	1.8657	35.8049
1.7394	2.9658	4600	1.8373	35.0353

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3