t5-asr-CV16

This model is a fine-tuned version of google/umt5-small on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.6296
• eval_wer: 0.8576
• eval_runtime: 86.6124
• eval_samples_per_second: 98.531
• eval_steps_per_second: 3.083
• epoch: 2.9929
• step: 900

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 256
• 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_ratio: 0.1
• num_epochs: 10

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu121
• Datasets 2.17.1
• Tokenizers 0.21.0