Edit model card

Visualize in Weights & Biases

deberta-finetuned-ner-microsoft-disaster

This model is a fine-tuned version of ML-GOD/deberta-finetuned-ner-microsoft-disaster on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1757
  • Precision: 0.9219
  • Recall: 0.9294
  • F1: 0.9257
  • Accuracy: 0.9797

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: 10

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.024 1.0 1799 0.1107 0.9149 0.9263 0.9206 0.9790
0.0201 2.0 3598 0.1197 0.9154 0.9225 0.9190 0.9782
0.014 3.0 5397 0.1249 0.9190 0.9279 0.9235 0.9794
0.0089 4.0 7196 0.1327 0.9151 0.9221 0.9186 0.9781
0.0057 5.0 8995 0.1432 0.9117 0.9268 0.9192 0.9789
0.0049 6.0 10794 0.1610 0.9164 0.9240 0.9202 0.9781
0.0031 7.0 12593 0.1740 0.9197 0.9273 0.9235 0.9791
0.0028 8.0 14392 0.1701 0.9222 0.9288 0.9255 0.9797
0.0022 9.0 16191 0.1750 0.9247 0.9290 0.9268 0.9799
0.0009 10.0 17990 0.1757 0.9219 0.9294 0.9257 0.9797

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1
Downloads last month
8
Safetensors
Model size
139M 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 ML-GOD/deberta-finetuned-ner-microsoft-disaster

Unable to build the model tree, the base model loops to the model itself. Learn more.