---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-pad-mult-clf-v2
  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-pad-mult-clf-v2

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: 0.5603
- Accuracy: 0.8182
- F1: 0.7530

## 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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 3    | 1.1843          | 0.5397   | 0.3783 |
| No log        | 2.0   | 6    | 1.0491          | 0.5397   | 0.3783 |
| No log        | 3.0   | 9    | 0.9692          | 0.5397   | 0.3783 |
| 1.1406        | 4.0   | 12   | 0.8981          | 0.5745   | 0.4501 |
| 1.1406        | 5.0   | 15   | 0.8277          | 0.7292   | 0.6618 |
| 1.1406        | 6.0   | 18   | 0.7654          | 0.7834   | 0.7178 |
| 0.862         | 7.0   | 21   | 0.7125          | 0.8046   | 0.7388 |
| 0.862         | 8.0   | 24   | 0.6680          | 0.8143   | 0.7480 |
| 0.862         | 9.0   | 27   | 0.6395          | 0.8162   | 0.7499 |
| 0.6971        | 10.0  | 30   | 0.6132          | 0.8162   | 0.7499 |
| 0.6971        | 11.0  | 33   | 0.5999          | 0.8182   | 0.7523 |
| 0.6971        | 12.0  | 36   | 0.5766          | 0.8221   | 0.7556 |
| 0.6971        | 13.0  | 39   | 0.5637          | 0.8221   | 0.7561 |
| 0.6012        | 14.0  | 42   | 0.5607          | 0.8182   | 0.7529 |
| 0.6012        | 15.0  | 45   | 0.5603          | 0.8182   | 0.7530 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0