metadata

library_name: peft
tags:
  - parquet
  - text-classification
datasets:
  - tweet_eval
metrics:
  - accuracy
base_model: Anthos23/FS-distilroberta-fine-tuned
model-index:
  - name: Anthos23_FS-distilroberta-fine-tuned-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: 0.694240837696335
            name: accuracy

Anthos23_FS-distilroberta-fine-tuned-finetuned-lora-tweet_eval_irony

This model is a fine-tuned version of Anthos23/FS-distilroberta-fine-tuned on the tweet_eval dataset. It achieves the following results on the evaluation set:

accuracy: 0.6942

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
0.4639	None	0
0.6293	0.7090	0
0.6010	0.6475	1
0.6545	0.6082	2
0.6995	0.5614	3
0.7005	0.5424	4
0.6806	0.5146	5
0.6932	0.5049	6
0.6942	0.4976	7

Framework versions

PEFT 0.8.2
Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.16.1
Tokenizers 0.15.2