---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ellis-v3-emotion-leadership
  results: []
---
NOTA: Este modelo será utilizado para comparação com a Versão 2.0.
Poderá ser excluido após esta validação/comparação


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# ellis-v3-emotion-leadership

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0202
- Accuracy: 0.8402

## 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: 70

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.6209        | 1.0   | 1479   | 0.5094          | 0.8014   |
| 0.4893        | 2.0   | 2958   | 0.4642          | 0.8166   |
| 0.4244        | 3.0   | 4437   | 0.4640          | 0.8284   |
| 0.3607        | 4.0   | 5916   | 0.4596          | 0.8333   |
| 0.3021        | 5.0   | 7395   | 0.4892          | 0.8322   |
| 0.2391        | 6.0   | 8874   | 0.5455          | 0.8288   |
| 0.2066        | 7.0   | 10353  | 0.6553          | 0.8288   |
| 0.1669        | 8.0   | 11832  | 0.6856          | 0.8387   |
| 0.1515        | 9.0   | 13311  | 0.8654          | 0.8280   |
| 0.1154        | 10.0  | 14790  | 0.8985          | 0.8322   |
| 0.094         | 11.0  | 16269  | 1.1159          | 0.8280   |
| 0.0822        | 12.0  | 17748  | 1.1954          | 0.8227   |
| 0.082         | 13.0  | 19227  | 1.2213          | 0.8341   |
| 0.0656        | 14.0  | 20706  | 1.2533          | 0.8375   |
| 0.0592        | 15.0  | 22185  | 1.3723          | 0.8284   |
| 0.0539        | 16.0  | 23664  | 1.4376          | 0.8326   |
| 0.0533        | 17.0  | 25143  | 1.4746          | 0.8291   |
| 0.044         | 18.0  | 26622  | 1.4234          | 0.8288   |
| 0.0411        | 19.0  | 28101  | 1.4971          | 0.8253   |
| 0.0343        | 20.0  | 29580  | 1.5132          | 0.8284   |
| 0.0359        | 21.0  | 31059  | 1.5020          | 0.8360   |
| 0.0309        | 22.0  | 32538  | 1.6418          | 0.8356   |
| 0.0416        | 23.0  | 34017  | 1.4984          | 0.8303   |
| 0.0314        | 24.0  | 35496  | 1.5713          | 0.8341   |
| 0.0316        | 25.0  | 36975  | 1.5679          | 0.8352   |
| 0.0281        | 26.0  | 38454  | 1.6399          | 0.8311   |
| 0.0179        | 27.0  | 39933  | 1.7032          | 0.8231   |
| 0.0326        | 28.0  | 41412  | 1.6551          | 0.8330   |
| 0.0178        | 29.0  | 42891  | 1.7136          | 0.8284   |
| 0.0149        | 30.0  | 44370  | 1.7317          | 0.8288   |
| 0.0211        | 31.0  | 45849  | 1.6790          | 0.8314   |
| 0.0221        | 32.0  | 47328  | 1.7909          | 0.8280   |
| 0.0179        | 33.0  | 48807  | 1.8027          | 0.8314   |
| 0.022         | 34.0  | 50286  | 1.7754          | 0.8299   |
| 0.0198        | 35.0  | 51765  | 1.7498          | 0.8295   |
| 0.0124        | 36.0  | 53244  | 1.8098          | 0.8356   |
| 0.0123        | 37.0  | 54723  | 1.8535          | 0.8261   |
| 0.0103        | 38.0  | 56202  | 1.8827          | 0.8345   |
| 0.0145        | 39.0  | 57681  | 1.8882          | 0.8303   |
| 0.0162        | 40.0  | 59160  | 1.8174          | 0.8326   |
| 0.0103        | 41.0  | 60639  | 1.8350          | 0.8368   |
| 0.0103        | 42.0  | 62118  | 1.7853          | 0.8390   |
| 0.0136        | 43.0  | 63597  | 1.7032          | 0.8368   |
| 0.0099        | 44.0  | 65076  | 1.8274          | 0.8318   |
| 0.0074        | 45.0  | 66555  | 1.8598          | 0.8333   |
| 0.0108        | 46.0  | 68034  | 1.7978          | 0.8413   |
| 0.0063        | 47.0  | 69513  | 1.8116          | 0.8364   |
| 0.0112        | 48.0  | 70992  | 1.8066          | 0.8356   |
| 0.0038        | 49.0  | 72471  | 1.9092          | 0.8352   |
| 0.005         | 50.0  | 73950  | 1.9159          | 0.8356   |
| 0.0035        | 51.0  | 75429  | 1.8669          | 0.8379   |
| 0.0067        | 52.0  | 76908  | 1.9222          | 0.8333   |
| 0.0049        | 53.0  | 78387  | 1.8417          | 0.8398   |
| 0.0034        | 54.0  | 79866  | 2.0452          | 0.8311   |
| 0.0056        | 55.0  | 81345  | 1.9375          | 0.8349   |
| 0.0014        | 56.0  | 82824  | 1.9941          | 0.8322   |
| 0.0004        | 57.0  | 84303  | 2.0133          | 0.8349   |
| 0.0017        | 58.0  | 85782  | 2.0038          | 0.8356   |
| 0.0009        | 59.0  | 87261  | 2.0347          | 0.8356   |
| 0.0015        | 60.0  | 88740  | 1.9901          | 0.8368   |
| 0.0014        | 61.0  | 90219  | 2.0233          | 0.8368   |
| 0.0022        | 62.0  | 91698  | 2.0148          | 0.8356   |
| 0.0012        | 63.0  | 93177  | 1.9823          | 0.8383   |
| 0.0014        | 64.0  | 94656  | 2.0099          | 0.8368   |
| 0.0034        | 65.0  | 96135  | 1.9925          | 0.8402   |
| 0.0009        | 66.0  | 97614  | 2.0088          | 0.8390   |
| 0.0006        | 67.0  | 99093  | 2.0141          | 0.8394   |
| 0.0           | 68.0  | 100572 | 2.0199          | 0.8417   |
| 0.0012        | 69.0  | 102051 | 2.0187          | 0.8394   |
| 0.0           | 70.0  | 103530 | 2.0202          | 0.8402   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.15.2