Jbautistas/checkpoints

Whisper large LoRA Merged Es - Jbautistas

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7153
• Wer: 58.9379

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• 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: 500
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.4943	6.2759	50	1.1849	58.2648
1.1692	12.5517	100	1.0537	56.2453
0.9958	18.8276	150	0.8947	54.8990
0.7308	25.0	200	0.7153	58.9379

Framework versions

• Transformers 4.56.0
• Pytorch 2.3.0+cu121
• Datasets 3.1.0
• Tokenizers 0.22.0