README.md

metadata

library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - ag_news
metrics:
  - accuracy
base_model: jb2k/bert-base-multilingual-cased-language-detection
model-index:
  - name: >-
      jb2k_bert-base-multilingual-cased-language-detection-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: 0.924078947368421
            name: accuracy

jb2k_bert-base-multilingual-cased-language-detection-finetuned-lora-ag_news

This model is a fine-tuned version of jb2k/bert-base-multilingual-cased-language-detection on the ag_news dataset. It achieves the following results on the evaluation set:

• accuracy: 0.9241

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
0.2504	None	0
0.9122	0.3431	0
0.9141	0.2605	1
0.9208	0.2356	2
0.9241	0.2231	3

Framework versions

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