README.md

metadata

library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - ag_news
metrics:
  - accuracy
base_model: dhimskyy/wiki-bert
model-index:
  - name: dhimskyy_wiki-bert-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: 0.8444736842105263
            name: accuracy

dhimskyy_wiki-bert-finetuned-lora-ag_news

This model is a fine-tuned version of dhimskyy/wiki-bert on the ag_news dataset. It achieves the following results on the evaluation set:

• accuracy: 0.8445

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
0.2471	None	0
0.8059	0.7762	0
0.8304	0.5563	1
0.8430	0.5109	2
0.8445	0.4907	3

Framework versions

• PEFT 0.8.2
• Transformers 4.37.2
• Pytorch 2.2.0
• Datasets 2.16.1
• Tokenizers 0.15.2