metadata

license: mit
base_model: microsoft/deberta-v3-base
tags:
  - multi-label text classification
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: deberta_classifier
    results: []

deberta_classifier

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0183
Accuracy: 0.9955
F1: 0.6062
Precision: 0.8225
Recall: 0.4799

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
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.6159	0.1169	100	0.5955	0.7621	0.0288	0.0148	0.4839
0.3536	0.2338	200	0.3085	0.9753	0.1645	0.1091	0.3341
0.1166	0.3507	300	0.0917	0.9931	0.4124	0.5429	0.3325
0.0456	0.4676	400	0.0375	0.9931	0.4124	0.5429	0.3325
0.0308	0.5845	500	0.0270	0.9931	0.4124	0.5429	0.3325
0.0249	0.7013	600	0.0234	0.9942	0.4459	0.7407	0.3189
0.0231	0.8182	700	0.0211	0.9953	0.5983	0.7970	0.4789
0.0213	0.9351	800	0.0196	0.9953	0.5989	0.7998	0.4787
0.0197	1.0520	900	0.0187	0.9954	0.6029	0.8168	0.4778
0.0205	1.1689	1000	0.0183	0.9955	0.6062	0.8225	0.4799
0.017	1.2858	1100	0.0175	0.9959	0.6610	0.8426	0.5437
0.018	1.4027	1200	0.0170	0.9960	0.6653	0.8685	0.5392
0.0177	1.5196	1300	0.0165	0.9961	0.6722	0.8732	0.5464
0.0189	1.6365	1400	0.0162	0.9962	0.6752	0.8910	0.5435
0.0179	1.7534	1500	0.0159	0.9964	0.6898	0.9151	0.5535
0.0169	1.8703	1600	0.0158	0.9964	0.6928	0.9030	0.5620
0.0172	1.9871	1700	0.0156	0.9964	0.6909	0.9130	0.5557

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1