Edit model card

SpeechT5-tuned-bn

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

  • Loss: 0.5572

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: 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: 100
  • training_steps: 1700
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.7601 0.1779 100 0.6865
0.7091 0.3559 200 0.6498
0.6819 0.5338 300 0.6345
0.6561 0.7117 400 0.6350
0.6353 0.8897 500 0.6044
0.6393 1.0676 600 0.5887
0.6402 1.2456 700 0.5906
0.6194 1.4235 800 0.5867
0.6127 1.6014 900 0.5788
0.608 1.7794 1000 0.5765
0.6129 1.9573 1100 0.5738
0.6044 2.1352 1200 0.5680
0.5894 2.3132 1300 0.5655
0.5952 2.4911 1400 0.5648
0.5963 2.6690 1500 0.5572
0.5889 2.8470 1600 0.5614
0.5897 3.0249 1700 0.5572

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.5.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.1
Downloads last month
33
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 Solo448/SpeechT5-tuned-bn

Finetuned
(780)
this model

Dataset used to train Solo448/SpeechT5-tuned-bn

Space using Solo448/SpeechT5-tuned-bn 1

Collection including Solo448/SpeechT5-tuned-bn