metadata

license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: deberta-v3-xsmall-Label_B-1280
    results: []

deberta-v3-xsmall-Label_B-1280

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

Loss: 0.1234
Accuracy: 0.9709
F1: 0.9708
Precision: 0.9719
Recall: 0.9709

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: 5e-05
train_batch_size: 5
eval_batch_size: 5
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 20
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0234	0.9999	2559	0.1234	0.9709	0.9708	0.9719	0.9709

Framework versions

Transformers 4.41.2
Pytorch 2.5.0+cu124
Datasets 2.18.0
Tokenizers 0.19.1