metadata

license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results
    results: []

results

This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1455
Accuracy: 0.9716

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: 5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6937	0.14	200	0.5659	0.8653
0.3263	0.27	400	0.2603	0.9248
0.2423	0.41	600	0.2538	0.9323
0.2036	0.55	800	0.2016	0.9495
0.1961	0.69	1000	0.1868	0.9519
0.1837	0.82	1200	0.1819	0.9537
0.2017	0.96	1400	0.1481	0.9626
0.1337	1.1	1600	0.1735	0.9597
0.097	1.23	1800	0.1684	0.9616
0.1059	1.37	2000	0.1545	0.9614
0.0968	1.51	2200	0.1436	0.9657
0.1147	1.64	2400	0.1401	0.9638
0.082	1.78	2600	0.1389	0.9673
0.078	1.92	2800	0.1233	0.9719
0.0668	2.06	3000	0.1373	0.9690
0.0279	2.19	3200	0.1512	0.9702
0.0331	2.33	3400	0.1353	0.9738
0.0276	2.47	3600	0.1404	0.9733
0.0339	2.6	3800	0.1527	0.9719
0.031	2.74	4000	0.1483	0.9710
0.0224	2.88	4200	0.1455	0.9716

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1