---
base_model: monologg/distilkobert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilkobert-KEmoFact-EFE-0927
  results: []
---

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# distilkobert-KEmoFact-EFE-0927

This model is a fine-tuned version of [monologg/distilkobert](https://huggingface.co/monologg/distilkobert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6353
- Precision: 0.1922
- Recall: 0.1524
- F1: 0.17
- Ov Accuracy: 0.7154
- Jaccard: 0.4371

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Ov Accuracy | Jaccard |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:-----------:|:-------:|
| No log        | 1.0   | 414  | 0.6729          | 0.1195    | 0.0967 | 0.1069 | 0.6943      | 0.3858  |
| 0.7003        | 2.0   | 828  | 0.6687          | 0.1438    | 0.1261 | 0.1344 | 0.6932      | 0.4298  |
| 0.6537        | 3.0   | 1242 | 0.6563          | 0.1463    | 0.1052 | 0.1224 | 0.7017      | 0.3558  |
| 0.64          | 4.0   | 1656 | 0.6613          | 0.1484    | 0.1160 | 0.1302 | 0.7019      | 0.3975  |
| 0.6323        | 5.0   | 2070 | 0.6563          | 0.1467    | 0.1160 | 0.1295 | 0.7028      | 0.3960  |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3