---
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: 0.2714
- F1: 0.4804
- Roc Auc: 0.6939
- Accuracy: 0.3110

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.2712        | 1.0   | 1037  | 0.2740          | 0.3755 | 0.6250  | 0.2680   |
| 0.2238        | 2.0   | 2074  | 0.2703          | 0.4161 | 0.6504  | 0.2749   |
| 0.1743        | 3.0   | 3111  | 0.2714          | 0.4804 | 0.6939  | 0.3110   |
| 0.143         | 4.0   | 4148  | 0.2838          | 0.4632 | 0.6811  | 0.2887   |
| 0.1089        | 5.0   | 5185  | 0.2971          | 0.4756 | 0.6897  | 0.3041   |
| 0.0874        | 6.0   | 6222  | 0.3242          | 0.4718 | 0.6965  | 0.2887   |
| 0.0726        | 7.0   | 7259  | 0.3414          | 0.4798 | 0.7003  | 0.3076   |
| 0.0565        | 8.0   | 8296  | 0.3538          | 0.4690 | 0.6897  | 0.2973   |
| 0.0501        | 9.0   | 9333  | 0.3712          | 0.4696 | 0.6959  | 0.2938   |
| 0.0426        | 10.0  | 10370 | 0.3692          | 0.4702 | 0.6922  | 0.2904   |


### Framework versions

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