m2nho/whisper-small-finetuned-atco2-asr-atcosim

Whisper small - Whisper with atcosim

This model is a fine-tuned version of openai/whisper-small on the This is a dataset constructed from two datasets: ATCOSIM. dataset. It achieves the following results on the evaluation set:

• Loss: 0.0385
• Wer: 1.4177

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: 50
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0349	0.2092	100	0.0974	6.4040
0.0493	0.4184	200	0.0664	3.2329
0.0464	0.6276	300	0.0519	2.8708
0.0394	0.8368	400	0.0474	2.3055
0.0177	1.0460	500	0.0429	1.7004
0.0054	1.2552	600	0.0416	1.5458
0.0182	1.4644	700	0.0411	1.5193
0.008	1.6736	800	0.0400	1.4663
0.0055	1.8828	900	0.0387	1.4619
0.0053	2.0921	1000	0.0385	1.4177

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1