---
license: cc-by-sa-4.0
base_model: aiknowyou/it-emotion-analyzer
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: it-emotion-analyzer_finetuned_pro_multilbel_emit
  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. -->

# it-emotion-analyzer_finetuned_pro_multilbel_emit

This model is a fine-tuned version of [aiknowyou/it-emotion-analyzer](https://huggingface.co/aiknowyou/it-emotion-analyzer) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3116
- F1: 0.5269
- Roc Auc: 0.7253
- Accuracy: 0.3643

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.2723        | 1.0   | 1037  | 0.2654          | 0.3992 | 0.6370  | 0.2801   |
| 0.2241        | 2.0   | 2074  | 0.2465          | 0.4387 | 0.6603  | 0.2973   |
| 0.1774        | 3.0   | 3111  | 0.2547          | 0.5066 | 0.7051  | 0.3608   |
| 0.1435        | 4.0   | 4148  | 0.2627          | 0.4834 | 0.6933  | 0.3333   |
| 0.1111        | 5.0   | 5185  | 0.2850          | 0.4992 | 0.7052  | 0.3540   |
| 0.0873        | 6.0   | 6222  | 0.3010          | 0.5112 | 0.7177  | 0.3505   |
| 0.0699        | 7.0   | 7259  | 0.3116          | 0.5269 | 0.7253  | 0.3643   |
| 0.054         | 8.0   | 8296  | 0.3288          | 0.5223 | 0.7246  | 0.3625   |
| 0.05          | 9.0   | 9333  | 0.3405          | 0.5149 | 0.7223  | 0.3608   |
| 0.0416        | 10.0  | 10370 | 0.3437          | 0.5196 | 0.7268  | 0.3591   |


### Framework versions

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