metadata

library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - tweet_eval
metrics:
  - accuracy
base_model: manueltonneau/bert-twitter-en-is-hired
model-index:
  - name: manueltonneau_bert-twitter-en-is-hired-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: 0.6565445026178011
            name: accuracy

manueltonneau_bert-twitter-en-is-hired-finetuned-lora-tweet_eval_irony

This model is a fine-tuned version of manueltonneau/bert-twitter-en-is-hired on the tweet_eval dataset. It achieves the following results on the evaluation set:

accuracy: 0.6565

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
0.5215	None	0
0.4984	0.9222	0
0.5497	0.7106	1
0.5916	0.6916	2
0.5969	0.6700	3
0.6272	0.6397	4
0.6199	0.6094	5
0.6314	0.5923	6
0.6565	0.5821	7

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.2