metadata

license: apache-2.0
library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - tweet_eval
metrics:
  - accuracy
base_model: Hate-speech-CNERG/bert-base-uncased-hatexplain-rationale-two
model-index:
  - name: >-
      Hate-speech-CNERG_bert-base-uncased-hatexplain-rationale-two-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: 0.6513089005235602
            name: accuracy

Hate-speech-CNERG_bert-base-uncased-hatexplain-rationale-two-finetuned-lora-tweet_eval_irony

This model is a fine-tuned version of Hate-speech-CNERG/bert-base-uncased-hatexplain-rationale-two on the tweet_eval dataset. It achieves the following results on the evaluation set:

accuracy: 0.6513

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
0.4932	None	0
0.6105	0.6865	0
0.5979	0.6589	1
0.6136	0.6218	2
0.6115	0.5979	3
0.6272	0.5751	4
0.6283	0.5581	5
0.6366	0.5483	6
0.6513	0.5348	7

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.2