whisper-small-ko-EYfreq – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
whisper-small-ko-EYfreq

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automatic-speech-recognition

hf-asr-leaderboard

generated_from_trainer

openai/whisper-small

endpoints_compatible

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whisper-small-ko-EYfreq

This model is a fine-tuned version of openai/whisper-small on the aihub Y dialogue dataset. It achieves the following results on the evaluation set:

Loss: 0.2161
Cer: 5.0021

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 50
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.2523	0.3	100	0.2529	6.6279
0.2278	0.59	200	0.2426	6.3193
0.2145	0.89	300	0.2306	6.3312
0.085	1.19	400	0.2142	5.5480
0.0793	1.48	500	0.2278	6.1354
0.0732	1.78	600	0.2077	5.2098
0.0266	2.07	700	0.2103	5.2394
0.0297	2.37	800	0.2074	4.9249
0.0267	2.67	900	0.2179	5.3759
0.0282	2.96	1000	0.2098	5.3522
0.0123	3.26	1100	0.2139	5.0436
0.009	3.56	1200	0.2142	5.0436
0.0096	3.85	1300	0.2189	5.2691
0.0043	4.15	1400	0.2137	4.9665
0.0036	4.44	1500	0.2146	4.9783
0.003	4.74	1600	0.2161	5.0021

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3