metadata

license: mit
base_model: ML-GOD/deberta-finetuned-ner-microsoft-disaster
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: deberta-finetuned-ner-microsoft-disaster
    results: []

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