whisper-medium-order

This model is a fine-tuned version of nandovallec/whisper-tiny-bg-l on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0173
  • Wer: 0.0

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: 1e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 64
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.624 3.0 5 1.4084 111.7647
0.5102 6.0 10 0.5733 43.1373
0.2173 8.78 15 0.3225 31.3725
0.0178 11.29 20 0.2035 27.4510
0.0138 14.0 25 0.1143 21.5686
0.036 17.0 30 0.0603 3.9216
0.0296 20.0 35 0.0366 1.9608
0.0074 22.59 40 0.0250 1.9608
0.0014 25.1 45 0.0191 0.0
0.0051 28.0 50 0.0173 0.0

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month
63
Safetensors
Model size
37.8M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Model tree for emonidi/whisper-medium-order

Finetuned
(2)
this model