README.md

metadata

library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - ag_news
metrics:
  - accuracy
base_model: Capreolus/bert-base-msmarco
model-index:
  - name: Capreolus_bert-base-msmarco-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: 0.9307894736842105
            name: accuracy

Capreolus_bert-base-msmarco-finetuned-lora-ag_news

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

• accuracy: 0.9308

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
0.2496	None	0
0.9187	0.3048	0
0.9267	0.2229	1
0.9289	0.2036	2
0.9308	0.1938	3

Framework versions

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