EGPABG

This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5020

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: 4
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 3000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.6281	0.2540	100	0.5862
0.6048	0.5079	200	0.5734
0.5792	0.7619	300	0.5444
0.57	1.0159	400	0.5418
0.5657	1.2698	500	0.5281
0.5625	1.5238	600	0.5301
0.5585	1.7778	700	0.5245
0.5559	2.0317	800	0.5263
0.5572	2.2857	900	0.5263
0.5527	2.5397	1000	0.5161
0.5524	2.7937	1100	0.5190
0.544	3.0476	1200	0.5154
0.542	3.3016	1300	0.5203
0.5425	3.5556	1400	0.5163
0.5413	3.8095	1500	0.5099
0.5328	4.0635	1600	0.5149
0.5406	4.3175	1700	0.5107
0.5347	4.5714	1800	0.5079
0.5362	4.8254	1900	0.5068
0.5355	5.0794	2000	0.5050
0.5312	5.3333	2100	0.5061
0.5282	5.5873	2200	0.5081
0.5298	5.8413	2300	0.5029
0.5288	6.0952	2400	0.5028
0.5371	6.3492	2500	0.5023
0.525	6.6032	2600	0.5022
0.5281	6.8571	2700	0.5039
0.5223	7.1111	2800	0.5023
0.5231	7.3651	2900	0.5022
0.5243	7.6190	3000	0.5020

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1