readme: ---
  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: 0.9616
  - Accuracy: 0.5103
  - F1: 0.4983
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.5782        | 1.0   | 15   | 1.4989          | 0.3448   | 0.2657 |
  | 1.5021        | 2.0   | 30   | 1.4732          | 0.3655   | 0.2645 |
  | 1.4674        | 3.0   | 45   | 1.4384          | 0.3448   | 0.2525 |
  | 1.4277        | 4.0   | 60   | 1.4140          | 0.3517   | 0.2751 |
  | 1.4341        | 5.0   | 75   | 1.3905          | 0.3379   | 0.2546 |
  | 1.3698        | 6.0   | 90   | 1.3697          | 0.3724   | 0.2936 |
  | 1.4233        | 7.0   | 105  | 1.3196          | 0.3862   | 0.3073 |
  | 1.3112        | 8.0   | 120  | 1.3048          | 0.4552   | 0.3958 |
  | 1.372         | 9.0   | 135  | 1.2548          | 0.4138   | 0.3385 |
  | 1.3284        | 10.0  | 150  | 1.2020          | 0.4759   | 0.4287 |
  | 1.2412        | 11.0  | 165  | 1.1672          | 0.4966   | 0.4594 |
  | 1.2508        | 12.0  | 180  | 1.1453          | 0.4897   | 0.4740 |
  | 1.1843        | 13.0  | 195  | 1.1172          | 0.4966   | 0.4784 |
  | 1.1694        | 14.0  | 210  | 1.1006          | 0.4966   | 0.4785 |
  | 1.1438        | 15.0  | 225  | 1.0763          | 0.5034   | 0.4851 |
  | 1.1066        | 16.0  | 240  | 1.0603          | 0.5034   | 0.4815 |
  | 1.1357        | 17.0  | 255  | 1.0435          | 0.5034   | 0.4821 |
  | 1.0352        | 18.0  | 270  | 1.0358          | 0.5034   | 0.4803 |
  | 1.1355        | 19.0  | 285  | 1.0183          | 0.5103   | 0.4941 |
  | 1.063         | 20.0  | 300  | 1.0063          | 0.5103   | 0.4957 |
  | 1.0329        | 21.0  | 315  | 0.9960          | 0.5103   | 0.4989 |
  | 1.063         | 22.0  | 330  | 0.9867          | 0.5103   | 0.4989 |
  | 1.0289        | 23.0  | 345  | 0.9821          | 0.5103   | 0.4980 |
  | 1.0624        | 24.0  | 360  | 0.9816          | 0.5103   | 0.4942 |
  | 1.0404        | 25.0  | 375  | 0.9723          | 0.5103   | 0.4939 |
  | 0.9791        | 26.0  | 390  | 0.9693          | 0.5103   | 0.4985 |
  | 1.0365        | 27.0  | 405  | 0.9663          | 0.5103   | 0.4980 |
  | 1.0129        | 28.0  | 420  | 0.9637          | 0.5103   | 0.5002 |
  | 0.9844        | 29.0  | 435  | 0.9617          | 0.5103   | 0.4997 |
  | 1.0049        | 30.0  | 450  | 0.9616          | 0.5103   | 0.4983 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.1
  - Datasets 2.6.1
  - Tokenizers 0.11.0
  