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---
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
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