Edit model card

acer_nitro_distilbert_turk

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

  • Loss: 0.7724
  • F1: 0.7596
  • Roc Auc: 0.8506
  • Accuracy: 0.6386

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
No log 1.0 166 0.6408 0.7330 0.8464 0.5904
No log 2.0 332 0.6674 0.7549 0.8434 0.6386
No log 3.0 498 0.7058 0.7573 0.8470 0.6145
0.3537 4.0 664 0.7887 0.7333 0.8358 0.6145
0.3537 5.0 830 0.8267 0.7586 0.8447 0.6265
0.3537 6.0 996 0.7217 0.7477 0.8491 0.6506
0.191 7.0 1162 0.7180 0.7593 0.8588 0.6506
0.191 8.0 1328 0.7742 0.7670 0.8531 0.6386
0.191 9.0 1494 0.7798 0.7560 0.8493 0.6265
0.1294 10.0 1660 0.7724 0.7596 0.8506 0.6386

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
Downloads last month
9
Safetensors
Model size
68.1M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for alionder/acer_nitro_distilbert_turk

Finetuned
(7)
this model