whisper-medium-hi-4cycles

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Whisper Hi - Gopika

This model is a fine-tuned version of openai/whisper-medium on the Konnakol dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.2581
• eval_wer: 0.0278
• eval_cer: 0.0297
• eval_half_cycle_error: 0.0278
• eval_full_cycle_error: 0.0532
• eval_runtime: 10.6512
• eval_samples_per_second: 2.159
• eval_steps_per_second: 0.188
• epoch: 125.0
• step: 750

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: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 1000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1