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_emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          config: emotion
          split: validation
          args: emotion
        metrics:
          - type: accuracy
            value: 0.7352941176470589
            name: accuracy

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

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: 0.7353

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: 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: 4

Training results

accuracy	train_loss	epoch
0.4037	None	0
0.5160	1.2275	0
0.6979	0.9809	1
0.7193	0.8033	2
0.7353	0.7538	3

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.2