whisper-atcosim3 – AI Model by luigisaetta | AlphaNeural AI

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whisper-atcosim3

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whisper-atcosim3

This model is a fine-tuned version of openai/whisper-medium on the atco2_atcosim dataset. It achieves the following results on the evaluation set:

Loss: 0.0476
Wer: 0.0198

Model description

This model is a special ASR model, derived doing fine-tuning of OpenAI Whisper model on ATC conversations. The base model is: OpenAI Whisper Medium

Intended uses & limitations

More information needed

Training and evaluation data

The model has been trained on the atco2_atcosim dataset.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 8
total_train_batch_size: 32
total_eval_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 150
training_steps: 600
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8218	0.2	50	0.3785	0.1451
0.1429	0.39	100	0.1213	0.0714
0.1155	0.59	150	0.0807	0.0517
0.0764	0.79	200	0.0652	0.0272
0.0724	0.98	250	0.0607	0.0393
0.0357	1.18	300	0.0569	0.0242
0.03	1.38	350	0.0553	0.0243
0.0325	1.57	400	0.0556	0.0228
0.03	1.77	450	0.0501	0.0242
0.0232	1.97	500	0.0485	0.0205
0.0143	2.16	550	0.0480	0.0194
0.0105	2.36	600	0.0476	0.0198

Framework versions

Transformers 4.29.0
Pytorch 2.0.0+cu117
Datasets 2.12.0
Tokenizers 0.11.0