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