base_04 – AI Model by Mehtap | AlphaNeural AI

You can deploy this model and start earning money today!

Mehtap/
base_04

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: 1.8804
Wer: 2.0146
Cer: 1.4030

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
1.4622	16.67	100	1.5376	0.8662	0.7357
0.297	33.33	200	1.2979	0.8675	0.6481
0.0163	50.0	300	1.5699	1.4066	1.0449
0.0034	66.67	400	1.6919	1.6416	1.1817
0.0017	83.33	500	1.7654	1.6943	1.2587
0.0011	100.0	600	1.8153	1.9908	1.4084
0.0008	116.67	700	1.8455	1.9817	1.3867
0.0007	133.33	800	1.8647	2.0479	1.4215
0.0006	150.0	900	1.8764	2.0489	1.4253
0.0006	166.67	1000	1.8804	2.0146	1.4030

Framework versions

Transformers 4.26.0
Pytorch 1.12.0+cu102
Datasets 2.9.0
Tokenizers 0.13.2