---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base_topic_classification_nyt_news
  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. -->

# roberta-base_topic_classification_nyt_news

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3797
- Accuracy: 0.9094
- F1: 0.9092
- Precision: 0.9098
- Recall: 0.9094

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3192        | 1.0   | 20480  | 0.4078          | 0.8865   | 0.8859 | 0.8892    | 0.8865 |
| 0.2863        | 2.0   | 40960  | 0.4271          | 0.8972   | 0.8970 | 0.8982    | 0.8972 |
| 0.1979        | 3.0   | 61440  | 0.3797          | 0.9094   | 0.9092 | 0.9098    | 0.9094 |
| 0.1239        | 4.0   | 81920  | 0.3981          | 0.9117   | 0.9113 | 0.9114    | 0.9117 |
| 0.1472        | 5.0   | 102400 | 0.4033          | 0.9137   | 0.9135 | 0.9134    | 0.9137 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2