metadata

license: mit
base_model: microsoft/deberta-v3-small
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: deeva-modcat-seqclass-deberta-v1
    results: []

deeva-modcat-seqclass-deberta-v1

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

Loss: 0.6435
Accuracy: 0.7161
F1: 0.2922
Precision: 0.1808
Recall: 0.7619

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: 24
eval_batch_size: 24
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	0.18	2	0.7148	0.4139	0.0476	0.0272	0.1905
No log	0.36	4	0.7027	0.4835	0.0408	0.0238	0.1429
No log	0.55	6	0.6917	0.5586	0.0474	0.0284	0.1429
No log	0.73	8	0.6817	0.5604	0.0476	0.0286	0.1429
No log	0.91	10	0.6727	0.5623	0.0478	0.0287	0.1429
No log	1.09	12	0.6648	0.6374	0.0571	0.0357	0.1429
No log	1.27	14	0.6578	0.6374	0.0571	0.0357	0.1429
No log	1.45	16	0.6521	0.6355	0.0569	0.0355	0.1429
No log	1.64	18	0.6477	0.6392	0.1005	0.0621	0.2619
No log	1.82	20	0.6448	0.7015	0.2419	0.1503	0.6190
No log	2.0	22	0.6435	0.7161	0.2922	0.1808	0.7619

Framework versions

Transformers 4.33.2
Pytorch 2.1.2+cu121
Datasets 2.14.5
Tokenizers 0.13.3