---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: summerschool-bert-irony
  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. -->

# ssummerschool-bert-irony

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8767
- Accuracy: 0.7015

## 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6792        | 0.2793 | 50   | 0.6678          | 0.5759   |
| 0.6489        | 0.5587 | 100  | 0.6514          | 0.6147   |
| 0.6282        | 0.8380 | 150  | 0.6360          | 0.6461   |
| 0.5746        | 1.1173 | 200  | 0.6596          | 0.6492   |
| 0.5325        | 1.3966 | 250  | 0.6253          | 0.6785   |
| 0.5431        | 1.6760 | 300  | 0.6226          | 0.6712   |
| 0.5058        | 1.9553 | 350  | 0.5896          | 0.6869   |
| 0.3982        | 2.2346 | 400  | 0.6467          | 0.6859   |
| 0.3837        | 2.5140 | 450  | 0.7012          | 0.6785   |
| 0.3714        | 2.7933 | 500  | 0.7326          | 0.6586   |
| 0.347         | 3.0726 | 550  | 0.7592          | 0.6702   |
| 0.247         | 3.3520 | 600  | 0.7466          | 0.6942   |
| 0.2382        | 3.6313 | 650  | 0.7514          | 0.6953   |
| 0.2304        | 3.9106 | 700  | 0.8268          | 0.6838   |
| 0.1716        | 4.1899 | 750  | 0.8822          | 0.6806   |
| 0.1631        | 4.4693 | 800  | 0.8698          | 0.6932   |
| 0.1435        | 4.7486 | 850  | 0.9178          | 0.6838   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1