---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: headlines_news_sentiment_distil
  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. -->

# headlines_news_sentiment_distil

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7839
- Model Preparation Time: 0.0033
- Accuracy: 0.8320
- F1: 0.8319

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:------:|
| 0.0132        | 1.0   | 504  | 1.8941          | 0.0033                 | 0.8244   | 0.8234 |
| 0.0071        | 2.0   | 1008 | 1.7813          | 0.0033                 | 0.8244   | 0.8244 |
| 0.0085        | 3.0   | 1512 | 1.7540          | 0.0033                 | 0.8337   | 0.8337 |
| 0.001         | 4.0   | 2016 | 1.7839          | 0.0033                 | 0.8320   | 0.8319 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1