license, tags, datasets, metrics, base_model, model-index

license	tags	datasets	metrics	base_model	model-index
apache-2.0	generated_from_trainer	fleurs	wer	openai/whisper-large-v2	name results whisper-large-v2-greek task dataset metrics type name automatic-speech-recognition Automatic Speech Recognition name type config split args fleurs fleurs el_gr test el_gr type value name wer 0.17739223993006523 Wer

whisper-large-v2-greek

This model is a fine-tuned version of openai/whisper-large-v2 on the fleurs dataset. It achieves the following results on the evaluation set:

• Loss: 0.2734
• Wer Ortho: 0.2102
• Wer: 0.1774

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: 2e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.1809	1.0	274	0.2244	0.2261	0.1947
0.0977	2.0	549	0.2306	0.2204	0.1856
0.0594	3.0	824	0.2332	0.2137	0.1814
0.0454	4.0	1099	0.2667	0.2315	0.1985
0.028	5.0	1374	0.2579	0.2151	0.1822
0.022	6.0	1649	0.2674	0.2188	0.1863
0.0202	6.98	1918	0.2734	0.2102	0.1774

Framework versions

• Transformers 4.30.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3