base_09 – AI Model by Mehtap | AlphaNeural AI

You can deploy this model and start earning money today!

Mehtap/
base_09

like

0

automatic-speech-recognition

hf-asr-leaderboard

generated_from_trainer

endpoints_compatible

Views

No views yet

base Turkish Whisper (bTW)

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

Loss: 1.4238
Wer: 0.9367
Cer: 0.7611

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: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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	Cer
1.6918	2.85	100	1.5023	0.7940	0.4289
0.6823	5.71	200	1.0475	0.8783	0.5573
0.4277	8.57	300	0.9944	0.8054	0.6120
0.2244	11.43	400	1.0460	0.6878	0.3825
0.1138	14.28	500	1.2059	0.7510	0.5020
0.0468	17.14	600	1.2180	1.1436	1.0719
0.0193	19.99	700	1.2801	1.1500	0.9344
0.0093	22.85	800	1.4574	0.9238	0.6799
0.0068	25.71	900	1.4137	0.9400	0.8128
0.0062	28.57	1000	1.4238	0.9367	0.7611

Framework versions

Transformers 4.26.0
Pytorch 1.12.0+cu102
Datasets 2.9.0
Tokenizers 0.13.2