---
library_name: peft
tags:
- parquet
- text-classification
datasets:
- tweet_eval
metrics:
- accuracy
base_model: anvay/finetuning-cardiffnlp-sentiment-model
model-index:
- name: anvay_finetuning-cardiffnlp-sentiment-model-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: 0.7696335078534031
      name: accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# anvay_finetuning-cardiffnlp-sentiment-model-finetuned-lora-tweet_eval_irony

This model is a fine-tuned version of [anvay/finetuning-cardiffnlp-sentiment-model](https://huggingface.co/anvay/finetuning-cardiffnlp-sentiment-model) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- accuracy: 0.7696

## 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 |
|:--------:|:----------:|:-----:|
| 0.4241   | None       | 0     |
| 0.6806   | 0.6581     | 0     |
| 0.7194   | 0.5688     | 1     |
| 0.7288   | 0.5244     | 2     |
| 0.7466   | 0.4909     | 3     |
| 0.7539   | 0.4672     | 4     |
| 0.7466   | 0.4497     | 5     |
| 0.7654   | 0.4388     | 6     |
| 0.7696   | 0.4364     | 7     |


### Framework versions

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