metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-large
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-small-obs-dataset
    results: []

whisper-small-obs-dataset

This model is a fine-tuned version of openai/whisper-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.3014
Wer: 87.4401

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: 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: 80
training_steps: 200
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.1319	1.0417	100	1.3716	119.4252
0.8298	2.0833	200	1.3014	87.4401

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu124
Datasets 2.21.0
Tokenizers 0.19.1