readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: TUF_ALBERT_5E
    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. -->
  
  # TUF_ALBERT_5E
  
  This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2389
  - Accuracy: 0.9533
  
  ## 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: 3e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.5099        | 0.1   | 50   | 0.3861          | 0.8533   |
  | 0.2985        | 0.2   | 100  | 0.2961          | 0.8933   |
  | 0.2972        | 0.3   | 150  | 0.2335          | 0.9333   |
  | 0.2835        | 0.4   | 200  | 0.1872          | 0.94     |
  | 0.26          | 0.5   | 250  | 0.4147          | 0.9133   |
  | 0.2986        | 0.59  | 300  | 0.2080          | 0.9267   |
  | 0.2554        | 0.69  | 350  | 0.3984          | 0.9133   |
  | 0.2306        | 0.79  | 400  | 0.2136          | 0.9333   |
  | 0.2218        | 0.89  | 450  | 0.4455          | 0.8867   |
  | 0.2113        | 0.99  | 500  | 0.2205          | 0.94     |
  | 0.2541        | 1.09  | 550  | 0.1705          | 0.9333   |
  | 0.1947        | 1.19  | 600  | 0.3264          | 0.8933   |
  | 0.2409        | 1.29  | 650  | 0.2084          | 0.92     |
  | 0.1968        | 1.39  | 700  | 0.2550          | 0.9267   |
  | 0.172         | 1.49  | 750  | 0.2238          | 0.9467   |
  | 0.1478        | 1.58  | 800  | 0.2501          | 0.9533   |
  | 0.2199        | 1.68  | 850  | 0.2618          | 0.9133   |
  | 0.1792        | 1.78  | 900  | 0.2109          | 0.9267   |
  | 0.1831        | 1.88  | 950  | 0.2641          | 0.92     |
  | 0.1534        | 1.98  | 1000 | 0.1924          | 0.94     |
  | 0.1208        | 2.08  | 1050 | 0.2990          | 0.9333   |
  | 0.1118        | 2.18  | 1100 | 0.4952          | 0.9      |
  | 0.158         | 2.28  | 1150 | 0.1706          | 0.9533   |
  | 0.1163        | 2.38  | 1200 | 0.1238          | 0.9733   |
  | 0.1738        | 2.48  | 1250 | 0.1989          | 0.9467   |
  | 0.1305        | 2.57  | 1300 | 0.4354          | 0.9067   |
  | 0.1668        | 2.67  | 1350 | 0.1276          | 0.9667   |
  | 0.1195        | 2.77  | 1400 | 0.2170          | 0.9533   |
  | 0.1057        | 2.87  | 1450 | 0.2882          | 0.9333   |
  | 0.1172        | 2.97  | 1500 | 0.1435          | 0.9667   |
  | 0.0893        | 3.07  | 1550 | 0.1754          | 0.96     |
  | 0.0582        | 3.17  | 1600 | 0.1858          | 0.96     |
  | 0.0887        | 3.27  | 1650 | 0.4954          | 0.92     |
  | 0.1166        | 3.37  | 1700 | 0.2356          | 0.9467   |
  | 0.0518        | 3.47  | 1750 | 0.1910          | 0.96     |
  | 0.0741        | 3.56  | 1800 | 0.1328          | 0.9733   |
  | 0.072         | 3.66  | 1850 | 0.2769          | 0.9467   |
  | 0.0534        | 3.76  | 1900 | 0.3501          | 0.94     |
  | 0.0776        | 3.86  | 1950 | 0.3171          | 0.94     |
  | 0.0537        | 3.96  | 2000 | 0.2138          | 0.9533   |
  | 0.0683        | 4.06  | 2050 | 0.2934          | 0.94     |
  | 0.015         | 4.16  | 2100 | 0.2233          | 0.9533   |
  | 0.0236        | 4.26  | 2150 | 0.2673          | 0.9533   |
  | 0.0357        | 4.36  | 2200 | 0.2279          | 0.96     |
  | 0.0298        | 4.46  | 2250 | 0.3017          | 0.9467   |
  | 0.0357        | 4.55  | 2300 | 0.2910          | 0.9467   |
  | 0.0208        | 4.65  | 2350 | 0.2498          | 0.9533   |
  | 0.0345        | 4.75  | 2400 | 0.2259          | 0.9667   |
  | 0.0174        | 4.85  | 2450 | 0.2274          | 0.9667   |
  | 0.0393        | 4.95  | 2500 | 0.2389          | 0.9533   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  