Edit model card

ceb_b32_le5_s8000

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: 0.3928

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: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 2000
  • training_steps: 8000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.5667 9.9010 500 0.4776
0.4838 19.8020 1000 0.4321
0.4604 29.7030 1500 0.4157
0.4373 39.6040 2000 0.4034
0.4359 49.5050 2500 0.4006
0.4236 59.4059 3000 0.3975
0.4196 69.3069 3500 0.3956
0.4183 79.2079 4000 0.3938
0.4148 89.1089 4500 0.3941
0.4034 99.0099 5000 0.3930
0.4137 108.9109 5500 0.3955
0.4094 118.8119 6000 0.3924
0.4112 128.7129 6500 0.3917
0.4041 138.6139 7000 0.3923
0.3989 148.5149 7500 0.3927
0.3989 158.4158 8000 0.3928

Framework versions

  • Transformers 4.41.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
Downloads last month
3
Safetensors
Model size
144M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for mikhail-panzo/ceb_b32_le5_s8000

Finetuned
(750)
this model