metadata

license: mit
library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - ag_news
metrics:
  - accuracy
base_model: roberta-base
model-index:
  - name: roberta-base-finetuned-lora-ag_news
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: ag_news
          type: ag_news
          config: default
          split: test
          args: default
        metrics:
          - type: accuracy
            value: 0.9402631578947368
            name: accuracy

roberta-base-finetuned-lora-ag_news

This model is a fine-tuned version of roberta-base on the ag_news dataset. It achieves the following results on the evaluation set:

accuracy: 0.9403

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: 0.0004
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: 4

Training results

accuracy	train_loss	epoch
0.1779	None	0
0.9337	0.2512	0
0.9370	0.1915	1
0.9392	0.1761	2
0.9403	0.1650	3

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.2