---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: distilbert-base-uncased
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: 0.9814
- Accuracy: 0.5103
- F1: 0.4950

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.5871        | 1.0   | 15   | 1.4971          | 0.3379   | 0.1821 |
| 1.4995        | 2.0   | 30   | 1.4588          | 0.3379   | 0.1707 |
| 1.464         | 3.0   | 45   | 1.4251          | 0.3655   | 0.2870 |
| 1.4105        | 4.0   | 60   | 1.4027          | 0.3793   | 0.2899 |
| 1.4269        | 5.0   | 75   | 1.3798          | 0.3793   | 0.2899 |
| 1.3835        | 6.0   | 90   | 1.3425          | 0.3724   | 0.3087 |
| 1.3885        | 7.0   | 105  | 1.3041          | 0.4069   | 0.3515 |
| 1.3286        | 8.0   | 120  | 1.3004          | 0.4621   | 0.4450 |
| 1.3572        | 9.0   | 135  | 1.2621          | 0.4345   | 0.3903 |
| 1.3176        | 10.0  | 150  | 1.2033          | 0.4552   | 0.4250 |
| 1.2509        | 11.0  | 165  | 1.1942          | 0.5034   | 0.4755 |
| 1.2781        | 12.0  | 180  | 1.1689          | 0.4828   | 0.4651 |
| 1.2156        | 13.0  | 195  | 1.1438          | 0.5034   | 0.4837 |
| 1.1518        | 14.0  | 210  | 1.1187          | 0.5034   | 0.4844 |
| 1.161         | 15.0  | 225  | 1.1013          | 0.5034   | 0.4858 |
| 1.1377        | 16.0  | 240  | 1.0882          | 0.5034   | 0.4796 |
| 1.1634        | 17.0  | 255  | 1.0692          | 0.5034   | 0.4860 |
| 1.0666        | 18.0  | 270  | 1.0591          | 0.5034   | 0.4772 |
| 1.1358        | 19.0  | 285  | 1.0455          | 0.5034   | 0.4736 |
| 1.1118        | 20.0  | 300  | 1.0313          | 0.5034   | 0.4872 |
| 1.0367        | 21.0  | 315  | 1.0228          | 0.5034   | 0.4853 |
| 1.0781        | 22.0  | 330  | 1.0106          | 0.5034   | 0.4857 |
| 1.0346        | 23.0  | 345  | 1.0034          | 0.5034   | 0.4935 |
| 1.1015        | 24.0  | 360  | 1.0032          | 0.5034   | 0.4806 |
| 1.0147        | 25.0  | 375  | 0.9911          | 0.5103   | 0.4903 |
| 1.0144        | 26.0  | 390  | 0.9856          | 0.5103   | 0.4972 |
| 1.022         | 27.0  | 405  | 0.9835          | 0.5103   | 0.4982 |
| 1.0218        | 28.0  | 420  | 0.9821          | 0.5103   | 0.4955 |
| 1.0173        | 29.0  | 435  | 0.9811          | 0.5103   | 0.4950 |
| 1.0241        | 30.0  | 450  | 0.9814          | 0.5103   | 0.4950 |


### Framework versions

- Transformers 4.24.0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.11.0