CNEC_1_1_robeczech-base

This model is a fine-tuned version of ufal/robeczech-base on the cnec dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3233
  • Precision: 0.8580
  • Recall: 0.8857
  • F1: 0.8716
  • Accuracy: 0.9511

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.3724 3.41 2000 0.3332 0.7990 0.8230 0.8108 0.9376
0.1863 6.81 4000 0.2656 0.8515 0.8636 0.8575 0.9455
0.1109 10.22 6000 0.2575 0.8505 0.8737 0.8619 0.9493
0.068 13.63 8000 0.2804 0.8567 0.8790 0.8677 0.9503
0.0466 17.04 10000 0.2952 0.8573 0.8830 0.8699 0.9498
0.0305 20.44 12000 0.2992 0.8618 0.8865 0.8740 0.9520
0.0231 23.85 14000 0.3272 0.8567 0.8843 0.8703 0.9512
0.02 27.26 16000 0.3233 0.8580 0.8857 0.8716 0.9511

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
Downloads last month
23
Safetensors
Model size
125M 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 stulcrad/CNEC_1_1_robeczech-base

Finetuned
(6)
this model

Evaluation results