---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: spillage-distilbert-base-uncased
  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. -->

# spillage-distilbert-base-uncased

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0785
- Accuracy: 0.6199

## 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: 70
- eval_batch_size: 70
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 23   | 1.3515          | 0.1956   |
| No log        | 2.0   | 46   | 1.2029          | 0.4133   |
| No log        | 3.0   | 69   | 1.0942          | 0.5092   |
| No log        | 4.0   | 92   | 0.9780          | 0.5793   |
| No log        | 5.0   | 115  | 0.9581          | 0.5609   |
| No log        | 6.0   | 138  | 1.0374          | 0.5756   |
| No log        | 7.0   | 161  | 1.0257          | 0.5941   |
| No log        | 8.0   | 184  | 1.0842          | 0.5941   |
| No log        | 9.0   | 207  | 1.1494          | 0.6052   |
| No log        | 10.0  | 230  | 1.2238          | 0.6273   |
| No log        | 11.0  | 253  | 1.2607          | 0.6421   |
| No log        | 12.0  | 276  | 1.3324          | 0.6052   |
| No log        | 13.0  | 299  | 1.5093          | 0.6199   |
| No log        | 14.0  | 322  | 1.5016          | 0.6273   |
| No log        | 15.0  | 345  | 1.6022          | 0.6384   |
| No log        | 16.0  | 368  | 1.6277          | 0.6273   |
| No log        | 17.0  | 391  | 1.7488          | 0.6384   |
| No log        | 18.0  | 414  | 1.9428          | 0.6273   |
| No log        | 19.0  | 437  | 1.8673          | 0.6273   |
| No log        | 20.0  | 460  | 1.8853          | 0.6273   |
| No log        | 21.0  | 483  | 1.9610          | 0.6347   |
| 0.2882        | 22.0  | 506  | 1.9328          | 0.6310   |
| 0.2882        | 23.0  | 529  | 1.9462          | 0.6421   |
| 0.2882        | 24.0  | 552  | 1.9936          | 0.6236   |
| 0.2882        | 25.0  | 575  | 2.0169          | 0.6236   |
| 0.2882        | 26.0  | 598  | 2.0216          | 0.6347   |
| 0.2882        | 27.0  | 621  | 2.0617          | 0.6310   |
| 0.2882        | 28.0  | 644  | 2.0578          | 0.6199   |
| 0.2882        | 29.0  | 667  | 2.0661          | 0.6236   |
| 0.2882        | 30.0  | 690  | 2.0785          | 0.6199   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.19.1