whisper-tiny-cit-nt – AI Model by Makkoen | AlphaNeural AI

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Makkoen/
whisper-tiny-cit-nt

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automatic-speech-recognition

generated_from_trainer

openai/whisper-tiny

endpoints_compatible

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Whisper tiny En - SF test

This model is a fine-tuned version of openai/whisper-tiny on the SF 200 dataset. It achieves the following results on the evaluation set:

Loss: 1.7031
Wer: 62.9291

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: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5292	8.8889	100	1.0957	59.9542
0.0462	17.7778	200	1.2314	57.6659
0.0058	26.6667	300	1.4473	63.6156
0.0029	35.5556	400	1.5361	63.6156
0.0017	44.4444	500	1.6016	60.6407
0.0012	53.3333	600	1.6367	62.9291
0.0009	62.2222	700	1.6670	63.6156
0.0008	71.1111	800	1.6875	63.6156
0.0007	80.0	900	1.6992	63.6156
0.0007	88.8889	1000	1.7031	62.9291

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1