---
library_name: transformers
license: apache-2.0
base_model: distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: time-period-classifier-bert
  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. -->

# time-period-classifier-bert

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1907
- Accuracy: 0.9674
- F1 Macro: 0.9683

## 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: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.1962        | 1.0   | 120  | 0.8911          | 0.6576   | 0.6000   |
| 0.8928        | 2.0   | 240  | 0.5397          | 0.7935   | 0.7938   |
| 0.565         | 3.0   | 360  | 0.4020          | 0.8605   | 0.8618   |
| 0.3721        | 4.0   | 480  | 0.2893          | 0.9094   | 0.9092   |
| 0.2123        | 5.0   | 600  | 0.2099          | 0.9438   | 0.9428   |
| 0.1374        | 6.0   | 720  | 0.1425          | 0.9692   | 0.9698   |
| 0.0682        | 7.0   | 840  | 0.1796          | 0.9656   | 0.9663   |
| 0.0451        | 8.0   | 960  | 0.1928          | 0.9674   | 0.9683   |
| 0.0275        | 9.0   | 1080 | 0.1870          | 0.9656   | 0.9666   |
| 0.0224        | 10.0  | 1200 | 0.1907          | 0.9674   | 0.9683   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.2.2
- Datasets 4.4.1
- Tokenizers 0.22.1