---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-IAM
  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-IAM

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: 0.9614
- Accuracy: 0.5103
- F1: 0.4923

## 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: 10
- eval_batch_size: 10
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.4993        | 1.0   | 15   | 1.4646          | 0.3379   | 0.1707 |
| 1.4661        | 2.0   | 30   | 1.4345          | 0.3379   | 0.1827 |
| 1.4397        | 3.0   | 45   | 1.3804          | 0.3793   | 0.2763 |
| 1.3817        | 4.0   | 60   | 1.3284          | 0.3931   | 0.2855 |
| 1.3375        | 5.0   | 75   | 1.2819          | 0.4207   | 0.3629 |
| 1.3073        | 6.0   | 90   | 1.2493          | 0.4621   | 0.4363 |
| 1.3085        | 7.0   | 105  | 1.2250          | 0.4828   | 0.4577 |
| 1.2545        | 8.0   | 120  | 1.2133          | 0.4966   | 0.4758 |
| 1.29          | 9.0   | 135  | 1.1806          | 0.5034   | 0.4776 |
| 1.2587        | 10.0  | 150  | 1.1522          | 0.5034   | 0.4764 |
| 1.2009        | 11.0  | 165  | 1.1269          | 0.4966   | 0.4760 |
| 1.2258        | 12.0  | 180  | 1.1133          | 0.4966   | 0.4734 |
| 1.1466        | 13.0  | 195  | 1.0942          | 0.5034   | 0.4699 |
| 1.1569        | 14.0  | 210  | 1.0735          | 0.5034   | 0.4793 |
| 1.1194        | 15.0  | 225  | 1.0616          | 0.5034   | 0.4832 |
| 1.0909        | 16.0  | 240  | 1.0529          | 0.5034   | 0.4560 |
| 1.153         | 17.0  | 255  | 1.0334          | 0.5034   | 0.4822 |
| 1.0086        | 18.0  | 270  | 1.0246          | 0.5034   | 0.4765 |
| 1.1102        | 19.0  | 285  | 1.0111          | 0.5103   | 0.4920 |
| 1.0967        | 20.0  | 300  | 1.0024          | 0.5103   | 0.4952 |
| 1.0265        | 21.0  | 315  | 0.9922          | 0.5103   | 0.4937 |
| 1.0377        | 22.0  | 330  | 0.9848          | 0.5103   | 0.4908 |
| 1.0156        | 23.0  | 345  | 0.9794          | 0.5103   | 0.4972 |
| 1.0807        | 24.0  | 360  | 0.9796          | 0.5103   | 0.4928 |
| 1.051         | 25.0  | 375  | 0.9726          | 0.5103   | 0.4831 |
| 0.9827        | 26.0  | 390  | 0.9675          | 0.5103   | 0.4972 |
| 1.0228        | 27.0  | 405  | 0.9646          | 0.5103   | 0.4951 |
| 1.0013        | 28.0  | 420  | 0.9627          | 0.5103   | 0.4950 |
| 0.9963        | 29.0  | 435  | 0.9617          | 0.5103   | 0.4938 |
| 0.9897        | 30.0  | 450  | 0.9614          | 0.5103   | 0.4923 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.1
- Datasets 2.6.1
- Tokenizers 0.11.0