---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ellis-v2-emotion-leadership
  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. -->

# ellis-v2-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: 0.7460
- Accuracy: 0.9411

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3621        | 1.0   | 1109  | 0.3042          | 0.8964   |
| 0.257         | 2.0   | 2218  | 0.2566          | 0.9259   |
| 0.1991        | 3.0   | 3327  | 0.2492          | 0.9274   |
| 0.1599        | 4.0   | 4436  | 0.2860          | 0.9320   |
| 0.1335        | 5.0   | 5545  | 0.2966          | 0.9299   |
| 0.1082        | 6.0   | 6654  | 0.3682          | 0.9274   |
| 0.0805        | 7.0   | 7763  | 0.3384          | 0.9381   |
| 0.056         | 8.0   | 8872  | 0.4321          | 0.9325   |
| 0.0391        | 9.0   | 9981  | 0.4476          | 0.9264   |
| 0.0431        | 10.0  | 11090 | 0.5036          | 0.9254   |
| 0.037         | 11.0  | 12199 | 0.4724          | 0.9315   |
| 0.032         | 12.0  | 13308 | 0.4975          | 0.9381   |
| 0.0248        | 13.0  | 14417 | 0.5242          | 0.9294   |
| 0.0194        | 14.0  | 15526 | 0.5792          | 0.9305   |
| 0.0309        | 15.0  | 16635 | 0.5574          | 0.9315   |
| 0.0309        | 16.0  | 17744 | 0.5071          | 0.9355   |
| 0.0223        | 17.0  | 18853 | 0.5156          | 0.9355   |
| 0.0235        | 18.0  | 19962 | 0.5363          | 0.9371   |
| 0.014         | 19.0  | 21071 | 0.6050          | 0.9294   |
| 0.0227        | 20.0  | 22180 | 0.5531          | 0.9371   |
| 0.0133        | 21.0  | 23289 | 0.6171          | 0.9355   |
| 0.0215        | 22.0  | 24398 | 0.5730          | 0.9320   |
| 0.0143        | 23.0  | 25507 | 0.5958          | 0.9330   |
| 0.0139        | 24.0  | 26616 | 0.5780          | 0.9335   |
| 0.0104        | 25.0  | 27725 | 0.6212          | 0.9315   |
| 0.0125        | 26.0  | 28834 | 0.6119          | 0.9335   |
| 0.007         | 27.0  | 29943 | 0.6179          | 0.9360   |
| 0.016         | 28.0  | 31052 | 0.6422          | 0.9355   |
| 0.0128        | 29.0  | 32161 | 0.6028          | 0.9360   |
| 0.007         | 30.0  | 33270 | 0.6751          | 0.9320   |
| 0.0109        | 31.0  | 34379 | 0.6579          | 0.9371   |
| 0.0055        | 32.0  | 35488 | 0.7140          | 0.9305   |
| 0.0116        | 33.0  | 36597 | 0.6488          | 0.9360   |
| 0.0138        | 34.0  | 37706 | 0.6029          | 0.9345   |
| 0.0095        | 35.0  | 38815 | 0.6393          | 0.9355   |
| 0.0041        | 36.0  | 39924 | 0.6387          | 0.9355   |
| 0.0063        | 37.0  | 41033 | 0.6304          | 0.9371   |
| 0.0037        | 38.0  | 42142 | 0.6349          | 0.9391   |
| 0.0077        | 39.0  | 43251 | 0.6230          | 0.9406   |
| 0.0027        | 40.0  | 44360 | 0.6546          | 0.9426   |
| 0.0022        | 41.0  | 45469 | 0.7147          | 0.9350   |
| 0.0054        | 42.0  | 46578 | 0.7450          | 0.9310   |
| 0.006         | 43.0  | 47687 | 0.6921          | 0.9360   |
| 0.0035        | 44.0  | 48796 | 0.6667          | 0.9376   |
| 0.0078        | 45.0  | 49905 | 0.6562          | 0.9371   |
| 0.0038        | 46.0  | 51014 | 0.6589          | 0.9376   |
| 0.0032        | 47.0  | 52123 | 0.6429          | 0.9371   |
| 0.0002        | 48.0  | 53232 | 0.6616          | 0.9386   |
| 0.0022        | 49.0  | 54341 | 0.6737          | 0.9416   |
| 0.0           | 50.0  | 55450 | 0.6911          | 0.9421   |
| 0.0004        | 51.0  | 56559 | 0.7703          | 0.9335   |
| 0.0047        | 52.0  | 57668 | 0.7535          | 0.9345   |
| 0.0003        | 53.0  | 58777 | 0.7973          | 0.9284   |
| 0.0026        | 54.0  | 59886 | 0.7266          | 0.9376   |
| 0.0047        | 55.0  | 60995 | 0.7328          | 0.9340   |
| 0.0           | 56.0  | 62104 | 0.7422          | 0.9371   |
| 0.0006        | 57.0  | 63213 | 0.7275          | 0.9371   |
| 0.0008        | 58.0  | 64322 | 0.7095          | 0.9396   |
| 0.0009        | 59.0  | 65431 | 0.7112          | 0.9401   |
| 0.0017        | 60.0  | 66540 | 0.6923          | 0.9421   |
| 0.0022        | 61.0  | 67649 | 0.7383          | 0.9376   |
| 0.0           | 62.0  | 68758 | 0.7314          | 0.9391   |
| 0.0004        | 63.0  | 69867 | 0.7433          | 0.9381   |
| 0.0           | 64.0  | 70976 | 0.7410          | 0.9386   |
| 0.0           | 65.0  | 72085 | 0.7519          | 0.9386   |
| 0.0003        | 66.0  | 73194 | 0.7459          | 0.9406   |
| 0.0004        | 67.0  | 74303 | 0.7366          | 0.9401   |
| 0.0           | 68.0  | 75412 | 0.7318          | 0.9411   |
| 0.0           | 69.0  | 76521 | 0.7430          | 0.9411   |
| 0.0           | 70.0  | 77630 | 0.7460          | 0.9411   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1