metadata

license: mit
base_model: microsoft/speecht5_tts
tags:
  - generated_from_trainer
datasets:
  - fleurs
model-index:
  - name: speecht5_finetuned_fleurs_zh_4000
    results: []

speecht5_finetuned_fleurs_zh_4000

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

Loss: 0.3888

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: 1e-05
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: 500
training_steps: 4000

Training results

Training Loss	Epoch	Step	Validation Loss
0.7366	1.09	100	0.6059
0.5892	2.19	200	0.5104
0.5436	3.28	300	0.4585
0.4848	4.38	400	0.4333
0.4733	5.47	500	0.4276
0.4534	6.57	600	0.4194
0.454	7.66	700	0.4172
0.4489	8.76	800	0.4111
0.4401	9.85	900	0.4108
0.441	10.94	1000	0.4136
0.437	12.04	1100	0.4078
0.4333	13.13	1200	0.4067
0.4328	14.23	1300	0.4002
0.4289	15.32	1400	0.4015
0.4254	16.42	1500	0.4012
0.427	17.51	1600	0.4020
0.4273	18.6	1700	0.4008
0.4222	19.7	1800	0.3966
0.4305	20.79	1900	0.3998
0.4198	21.89	2000	0.3954
0.4225	22.98	2100	0.3961
0.4223	24.08	2200	0.3965
0.4201	25.17	2300	0.3922
0.4234	26.27	2400	0.3939
0.4213	27.36	2500	0.3930
0.4182	28.45	2600	0.3934
0.4119	29.55	2700	0.3925
0.4113	30.64	2800	0.3907
0.4131	31.74	2900	0.3907
0.4135	32.83	3000	0.3933
0.4142	33.93	3100	0.3909
0.4144	35.02	3200	0.3919
0.414	36.11	3300	0.3919
0.418	37.21	3400	0.3899
0.4094	38.3	3500	0.3897
0.4149	39.4	3600	0.3924
0.4105	40.49	3700	0.3905
0.413	41.59	3800	0.3895
0.4117	42.68	3900	0.3900
0.4096	43.78	4000	0.3888

Framework versions

Transformers 4.33.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3