metadata

base_model: openai/whisper-small
datasets:
  - lord-reso/inbrowser-proctor-dataset
language:
  - en
library_name: peft
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: Whisper-Small-Inbrowser-Proctor-LORA
    results: []

Whisper-Small-Inbrowser-Proctor-LORA

This model is a fine-tuned version of openai/whisper-small on the Inbrowser Procotor Dataset dataset. It achieves the following results on the evaluation set:

eval_loss: 0.3714
eval_wer: 20.6913
eval_runtime: 58.8679
eval_samples_per_second: 1.189
eval_steps_per_second: 0.153
epoch: 9.8214
step: 275

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-06
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP

Framework versions

PEFT 0.12.1.dev0
Transformers 4.45.0.dev0
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1