---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-stationary-update
  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. -->

# distilbert-base-uncased-finetuned-stationary-update

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: 0.7730
- Accuracy: 0.7833
- F1: 0.7806

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6079        | 1.0   | 38   | 0.5325          | 0.7      | 0.6134 |
| 0.4686        | 2.0   | 76   | 0.4729          | 0.7867   | 0.7849 |
| 0.3713        | 3.0   | 114  | 0.4896          | 0.8033   | 0.8009 |
| 0.2955        | 4.0   | 152  | 0.5363          | 0.78     | 0.7782 |
| 0.2141        | 5.0   | 190  | 0.6037          | 0.7867   | 0.7782 |
| 0.1664        | 6.0   | 228  | 0.6722          | 0.7633   | 0.7554 |
| 0.1343        | 7.0   | 266  | 0.6951          | 0.79     | 0.7829 |
| 0.0854        | 8.0   | 304  | 0.7358          | 0.77     | 0.7678 |
| 0.0888        | 9.0   | 342  | 0.7616          | 0.7767   | 0.7724 |
| 0.0669        | 10.0  | 380  | 0.7730          | 0.7833   | 0.7806 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0