metadata

base_model: openai/whisper-medium
datasets:
  - miosipof/asr_en
language:
  - en
library_name: peft
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: Whisper Medium
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: miosipof/asr_en
          type: miosipof/asr_en
          config: default
          split: train
          args: default
        metrics:
          - type: wer
            value: 20.578778135048232
            name: Wer

Whisper Medium

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

Loss: 0.3170
Wer: 20.5788

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: 0.001
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 32
training_steps: 128
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.8843	1.0847	32	0.8819	135.0482
0.3624	2.1695	64	0.3312	47.1061
0.1637	3.2542	96	0.3231	22.1865
0.0903	4.3390	128	0.3170	20.5788

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1