---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-uncased_3epoch10
  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. -->

# distilbert-base-uncased_3epoch10

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5208
- Accuracy: 0.6988
- F1: 0.3192
- Precision: 0.4537
- Recall: 0.2462
- Precision Sarcastic: 0.4537
- Recall Sarcastic: 0.2462
- F1 Sarcastic: 0.3192

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log        | 1.0   | 174  | 2.6411          | 0.7017   | 0.1481 | 0.4091    | 0.0905 | 0.4091              | 0.0905           | 0.1481       |
| No log        | 2.0   | 348  | 2.0172          | 0.7104   | 0.3045 | 0.4889    | 0.2211 | 0.4889              | 0.2211           | 0.3045       |
| 0.0495        | 3.0   | 522  | 1.9688          | 0.6844   | 0.4097 | 0.4419    | 0.3819 | 0.4419              | 0.3819           | 0.4097       |
| 0.0495        | 4.0   | 696  | 2.1007          | 0.7075   | 0.2671 | 0.4744    | 0.1859 | 0.4744              | 0.1859           | 0.2671       |
| 0.0495        | 5.0   | 870  | 2.4142          | 0.7104   | 0.2744 | 0.4872    | 0.1910 | 0.4872              | 0.1910           | 0.2744       |
| 0.032         | 6.0   | 1044 | 2.3684          | 0.6931   | 0.4132 | 0.4573    | 0.3769 | 0.4573              | 0.3769           | 0.4132       |
| 0.032         | 7.0   | 1218 | 2.5365          | 0.7118   | 0.2754 | 0.4935    | 0.1910 | 0.4935              | 0.1910           | 0.2754       |
| 0.032         | 8.0   | 1392 | 2.5712          | 0.7046   | 0.2756 | 0.4643    | 0.1960 | 0.4643              | 0.1960           | 0.2756       |
| 0.0112        | 9.0   | 1566 | 2.4974          | 0.6960   | 0.3127 | 0.4444    | 0.2412 | 0.4444              | 0.2412           | 0.3127       |
| 0.0112        | 10.0  | 1740 | 2.5208          | 0.6988   | 0.3192 | 0.4537    | 0.2462 | 0.4537              | 0.2462           | 0.3192       |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1