---
base_model: MilaNLProc/feel-it-italian-emotion
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: multilabel_emotion_classification_finetuned_multimodal
  results: []
---

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

This model is a fine-tuned version of [MilaNLProc/feel-it-italian-emotion](https://huggingface.co/MilaNLProc/feel-it-italian-emotion) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3025
- F1: 0.2543
- Roc Auc: 0.5733
- Accuracy: 0.2464

## 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: 16
- eval_batch_size: 16
- 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   | 35   | 0.4602          | 0.2394 | 0.5743  | 0.1884   |
| No log        | 2.0   | 70   | 0.3852          | 0.0    | 0.5     | 0.1087   |
| No log        | 3.0   | 105  | 0.3511          | 0.0    | 0.5     | 0.1087   |
| No log        | 4.0   | 140  | 0.3328          | 0.0    | 0.5     | 0.1087   |
| No log        | 5.0   | 175  | 0.3221          | 0.0    | 0.5     | 0.1087   |
| No log        | 6.0   | 210  | 0.3154          | 0.0136 | 0.5034  | 0.1159   |
| No log        | 7.0   | 245  | 0.3103          | 0.0789 | 0.5205  | 0.1449   |
| No log        | 8.0   | 280  | 0.3064          | 0.1274 | 0.5338  | 0.1739   |
| No log        | 9.0   | 315  | 0.3036          | 0.2442 | 0.5699  | 0.2391   |
| No log        | 10.0  | 350  | 0.3025          | 0.2543 | 0.5733  | 0.2464   |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.11.0
- Datasets 2.18.0
- Tokenizers 0.15.2