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---
base_model: lupobricco/irony_classification_single_label_base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ironita_finetuned_singlelabel_no_correlations
  results: []
---

<!-- 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. -->

# ironita_finetuned_singlelabel_no_correlations

This model is a fine-tuned version of [lupobricco/irony_classification_single_label_base](https://huggingface.co/lupobricco/irony_classification_single_label_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0734
- Accuracy: 0.8162
- F1: 0.4358

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4699        | 1.0   | 715  | 0.6672          | 0.8316   | 0.4141 |
| 0.2082        | 2.0   | 1430 | 1.0734          | 0.8162   | 0.4358 |
| 0.0699        | 3.0   | 2145 | 1.2288          | 0.8179   | 0.4059 |
| 0.0356        | 4.0   | 2860 | 1.2345          | 0.8213   | 0.4194 |
| 0.0245        | 5.0   | 3575 | 1.3995          | 0.8265   | 0.4007 |
| 0.0137        | 6.0   | 4290 | 1.4029          | 0.8230   | 0.4222 |
| 0.0166        | 7.0   | 5005 | 1.4924          | 0.8213   | 0.4000 |
| 0.0079        | 8.0   | 5720 | 1.5032          | 0.8299   | 0.3961 |
| 0.0126        | 9.0   | 6435 | 1.5878          | 0.8213   | 0.4285 |
| 0.0046        | 10.0  | 7150 | 1.5537          | 0.8213   | 0.4050 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1