Edit model card

speecht5_finetuned_voxpopuli_es

This model is a fine-tuned version of KGSAGAR/speecht5_finetuned_voxpopuli_es on the voxpopuli dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5950

Model description

More information needed

Intended uses & limitations

(https://colab.research.google.com/drive/1NG4uTeW97wYRdzkjfWI4gONntxg9Y17S?usp=sharing)__ To enhance the model's performance, it is advisable to increase the training steps parameter and carry out further training.

Training and evaluation data

TrainOutput(global_step=25, training_loss=0.6927243232727051, metrics={'train_runtime': 8513.8366, 'train_samples_per_second': 0.094, 'train_steps_per_second': 0.003, 'total_flos': 116396101622592.0, 'train_loss': 0.6927243232727051, 'epoch': 0.11})

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-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: 5
  • training_steps: 25

Training results

Training Loss Epoch Step Validation Loss
0.7148 0.02 5 0.6356
0.7004 0.04 10 0.6357
0.6845 0.06 15 0.6040
0.6813 0.09 20 0.5962
0.6827 0.11 25 0.5950

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
Downloads last month
2
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 KGSAGAR/speecht5_finetuned_voxpopuli_es

Unable to build the model tree, the base model loops to the model itself. Learn more.