electra-srb-ner-setimes

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2804
  • Precision: 0.8286
  • Recall: 0.8081
  • F1: 0.8182
  • Accuracy: 0.9547

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 104 0.2981 0.6737 0.6113 0.6410 0.9174
No log 2.0 208 0.2355 0.7279 0.6701 0.6978 0.9307
No log 3.0 312 0.2079 0.7707 0.7062 0.7371 0.9402
No log 4.0 416 0.2078 0.7689 0.7479 0.7582 0.9449
0.2391 5.0 520 0.2089 0.8083 0.7476 0.7767 0.9484
0.2391 6.0 624 0.2199 0.7981 0.7726 0.7851 0.9487
0.2391 7.0 728 0.2528 0.8205 0.7749 0.7971 0.9511
0.2391 8.0 832 0.2265 0.8074 0.8003 0.8038 0.9524
0.2391 9.0 936 0.2843 0.8265 0.7716 0.7981 0.9504
0.0378 10.0 1040 0.2450 0.8024 0.8019 0.8021 0.9520
0.0378 11.0 1144 0.2550 0.8116 0.7986 0.8051 0.9519
0.0378 12.0 1248 0.2706 0.8208 0.7957 0.8081 0.9532
0.0378 13.0 1352 0.2664 0.8040 0.8035 0.8038 0.9530
0.0378 14.0 1456 0.2571 0.8011 0.8110 0.8060 0.9529
0.0099 15.0 1560 0.2673 0.8051 0.8129 0.8090 0.9534
0.0099 16.0 1664 0.2733 0.8074 0.8087 0.8081 0.9529
0.0099 17.0 1768 0.2835 0.8254 0.8074 0.8163 0.9543
0.0099 18.0 1872 0.2771 0.8222 0.8081 0.8151 0.9545
0.0099 19.0 1976 0.2776 0.8237 0.8084 0.8160 0.9546
0.0044 20.0 2080 0.2804 0.8286 0.8081 0.8182 0.9547

Framework versions

  • Transformers 4.9.2
  • Pytorch 1.9.0
  • Datasets 1.11.0
  • Tokenizers 0.10.1
Downloads last month
13
Safetensors
Model size
109M params
Tensor type
I64
·
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.