metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - deepinfinityai/30_NLEM_Aug_audios_dataset
metrics:
  - wer
model-index:
  - name: v03_Med_30_NLEM_Aug_Tablets_Model
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: /30_NLEM_Aug_audios_dataset
          type: deepinfinityai/30_NLEM_Aug_audios_dataset
        metrics:
          - name: Wer
            type: wer
            value: 0

v03_Med_30_NLEM_Aug_Tablets_Model

This model is a fine-tuned version of openai/whisper-medium on the /30_NLEM_Aug_audios_dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.0001
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: 4
eval_batch_size: 8
seed: 42
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: 10
training_steps: 218
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0899	1.0	44	0.0198	2.8571
0.0007	2.0	88	0.0001	0.0
0.0001	3.0	132	0.0001	0.0
0.0001	4.0	176	0.0001	0.0

Framework versions

Transformers 4.50.3
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0