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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ironita_finetuned_correlations

This model is a fine-tuned version of [lupobricco/irony_classification_ita_base](https://huggingface.co/lupobricco/irony_classification_ita_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2372
- F1: 0.5152
- Roc Auc: 0.7176
- Accuracy: 0.8419

## 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 | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 291  | 0.2090          | 0.35   | 0.6183  | 0.8282   |
| 0.2333        | 2.0   | 582  | 0.2372          | 0.5152 | 0.7176  | 0.8419   |
| 0.2333        | 3.0   | 873  | 0.3356          | 0.3924 | 0.6345  | 0.8436   |
| 0.1292        | 4.0   | 1164 | 0.3644          | 0.3399 | 0.6114  | 0.8351   |
| 0.1292        | 5.0   | 1455 | 0.4006          | 0.2973 | 0.5933  | 0.8316   |
| 0.0666        | 6.0   | 1746 | 0.4199          | 0.3288 | 0.6045  | 0.8402   |
| 0.0346        | 7.0   | 2037 | 0.4441          | 0.4134 | 0.6552  | 0.8282   |
| 0.0346        | 8.0   | 2328 | 0.4483          | 0.4382 | 0.6659  | 0.8385   |
| 0.019         | 9.0   | 2619 | 0.4600          | 0.4070 | 0.6483  | 0.8333   |
| 0.019         | 10.0  | 2910 | 0.4580          | 0.4432 | 0.6668  | 0.8402   |


### Framework versions

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