---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: summerschool-bert-massive
  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. -->

# summerschool-bert-massive

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: 0.8479
- Accuracy: 0.8283
- F1: 0.8139

## 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 3.8604        | 0.1389 | 100  | 3.3964          | 0.2720   | 0.2091 |
| 3.046         | 0.2778 | 200  | 2.5353          | 0.4870   | 0.3971 |
| 2.3977        | 0.4167 | 300  | 2.0141          | 0.6193   | 0.5592 |
| 1.9293        | 0.5556 | 400  | 1.6738          | 0.6803   | 0.6328 |
| 1.6997        | 0.6944 | 500  | 1.4307          | 0.7334   | 0.6937 |
| 1.505         | 0.8333 | 600  | 1.2759          | 0.7772   | 0.7469 |
| 1.3531        | 0.9722 | 700  | 1.1656          | 0.7757   | 0.7445 |
| 1.1651        | 1.1111 | 800  | 1.0720          | 0.7914   | 0.7707 |
| 1.0441        | 1.25   | 900  | 0.9979          | 0.8032   | 0.7838 |
| 1.0021        | 1.3889 | 1000 | 0.9496          | 0.8146   | 0.7977 |
| 0.9732        | 1.5278 | 1100 | 0.8996          | 0.8278   | 0.8116 |
| 0.9025        | 1.6667 | 1200 | 0.8816          | 0.8214   | 0.8053 |
| 0.8952        | 1.8056 | 1300 | 0.8612          | 0.8273   | 0.8128 |
| 0.8435        | 1.9444 | 1400 | 0.8479          | 0.8283   | 0.8139 |


### Framework versions

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