Edit model card

gecco-german-counseling-gbert-base

This model is a fine-tuned version of deepset/gbert-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2480
  • Accuracy: 0.7194
  • F1: 0.5062

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
3.439 1.0 20 3.1181 0.2484 0.0474
2.9431 2.0 40 2.6841 0.3935 0.1637
2.5477 3.0 60 2.3120 0.5387 0.2802
2.1823 4.0 80 2.0526 0.5935 0.3138
1.8786 5.0 100 1.8242 0.6387 0.3541
1.6267 6.0 120 1.6720 0.6548 0.3682
1.4447 7.0 140 1.5538 0.6645 0.3718
1.2734 8.0 160 1.4655 0.6710 0.3801
1.1099 9.0 180 1.4040 0.6935 0.4202
1.0766 10.0 200 1.3541 0.6903 0.4330
0.913 11.0 220 1.3078 0.6968 0.4629
0.8557 12.0 240 1.2879 0.7161 0.5000
0.8477 13.0 260 1.2772 0.7097 0.4946
0.7412 14.0 280 1.2598 0.7161 0.5042
0.7341 15.0 300 1.2484 0.7194 0.5069
0.7029 16.0 320 1.2480 0.7194 0.5062

Framework versions

  • Transformers 4.35.1
  • Pytorch 1.10.1+cu111
  • Datasets 2.14.7
  • Tokenizers 0.14.1
Downloads last month
10
Safetensors
Model size
110M 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 th-nuernberg/gbert-base-german-counseling-gecco

Base model

deepset/gbert-base
Finetuned
(46)
this model