README.md

metadata

license: agpl-3.0
library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - tweet_eval
metrics:
  - accuracy
base_model: vesteinn/XLMR-ENIS-finetuned-cola
model-index:
  - name: vesteinn_XLMR-ENIS-finetuned-cola-finetuned-lora-tweet_eval_irony
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          config: irony
          split: validation
          args: irony
        metrics:
          - type: accuracy
            value: 0.6408376963350786
            name: accuracy

vesteinn_XLMR-ENIS-finetuned-cola-finetuned-lora-tweet_eval_irony

This model is a fine-tuned version of vesteinn/XLMR-ENIS-finetuned-cola on the tweet_eval dataset. It achieves the following results on the evaluation set:

• accuracy: 0.6408

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: 0.0005
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8

Training results

accuracy	train_loss	epoch
0.5424	None	0
0.5990	0.7131	0
0.5791	0.6680	1
0.6188	0.6512	2
0.6220	0.6311	3
0.6251	0.6118	4
0.5874	0.5950	5
0.6230	0.5831	6
0.6408	0.5857	7

Framework versions

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