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---
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: 0.6265
- Model Preparation Time: 0.0026
- Accuracy: 0.8423
- F1: 0.8423
## 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 | Model Preparation Time | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:------:|
| 0.4834 | 1.0 | 504 | 0.4035 | 0.0026 | 0.8156 | 0.8156 |
| 0.3402 | 2.0 | 1008 | 0.3987 | 0.0026 | 0.8343 | 0.8343 |
| 0.2343 | 3.0 | 1512 | 0.4514 | 0.0026 | 0.8392 | 0.8391 |
| 0.1604 | 4.0 | 2016 | 0.5443 | 0.0026 | 0.8396 | 0.8396 |
| 0.1151 | 5.0 | 2520 | 0.6265 | 0.0026 | 0.8423 | 0.8423 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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