speecht5_finetuned_google_fleurs_greek

This model is a fine-tuned version of microsoft/speecht5_tts on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3920

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: 2.5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• 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
• num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss
0.5174	1.0	583	0.4863
0.4948	2.0	1166	0.4611
0.4723	3.0	1749	0.4503
0.4763	4.0	2333	0.4438
0.4614	5.0	2916	0.4407
0.4569	6.0	3499	0.4387
0.4538	7.0	4082	0.4306
0.4539	8.0	4666	0.4282
0.4564	9.0	5249	0.4230
0.4493	10.0	5832	0.4222
0.445	11.0	6415	0.4190
0.4564	12.0	6999	0.4195
0.4381	13.0	7582	0.4161
0.4328	14.0	8165	0.4147
0.4424	15.0	8748	0.4140
0.4282	16.0	9332	0.4117
0.4349	17.0	9915	0.4090
0.4381	18.0	10498	0.4090
0.4328	19.0	11081	0.4073
0.4347	20.0	11665	0.4079
0.4293	21.0	12248	0.4055
0.4251	22.0	12831	0.4052
0.4359	23.0	13414	0.4023
0.4311	24.0	13998	0.4016
0.421	25.0	14581	0.4014
0.4162	26.0	15164	0.3991
0.4219	27.0	15747	0.3990
0.4247	28.0	16331	0.3989
0.4188	29.0	16914	0.3974
0.4229	30.0	17497	0.3976
0.4246	31.0	18080	0.3960
0.4219	32.0	18664	0.3956
0.4228	33.0	19247	0.3951
0.4183	34.0	19830	0.3946
0.4097	35.0	20413	0.3936
0.4245	36.0	20997	0.3935
0.4184	37.0	21580	0.3930
0.4198	38.0	22163	0.3937
0.4193	39.0	22746	0.3925
0.4096	39.98	23320	0.3920

Framework versions

• Transformers 4.30.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3