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---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: News_classification_distilbert
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. -->
# News_classification_distilbert
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1001
- F1: 0.9786
- Acc: 0.9795
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 400
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Acc |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.1312 | 1.0 | 3868 | 0.0919 | 0.9760 | 0.9771 |
| 0.063 | 2.0 | 7736 | 0.0884 | 0.9785 | 0.9794 |
| 0.0396 | 3.0 | 11604 | 0.1001 | 0.9786 | 0.9795 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3