readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: SST2_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. -->
  
  # SST2_ALBERT_5E
  
  This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5698
  - Accuracy: 0.8933
  
  ## 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: 1e-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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.5574        | 0.12  | 50   | 0.4424          | 0.8      |
  | 0.4078        | 0.23  | 100  | 0.3995          | 0.8533   |
  | 0.3594        | 0.35  | 150  | 0.3805          | 0.8533   |
  | 0.2952        | 0.46  | 200  | 0.3388          | 0.8933   |
  | 0.3157        | 0.58  | 250  | 0.3629          | 0.8733   |
  | 0.2623        | 0.69  | 300  | 0.5120          | 0.8667   |
  | 0.261         | 0.81  | 350  | 0.2851          | 0.8867   |
  | 0.3071        | 0.92  | 400  | 0.2754          | 0.8733   |
  | 0.2905        | 1.04  | 450  | 0.3013          | 0.8867   |
  | 0.2114        | 1.15  | 500  | 0.3205          | 0.9      |
  | 0.2537        | 1.27  | 550  | 0.4157          | 0.8867   |
  | 0.2106        | 1.39  | 600  | 0.5170          | 0.86     |
  | 0.2227        | 1.5   | 650  | 0.3422          | 0.9      |
  | 0.2304        | 1.62  | 700  | 0.5696          | 0.8533   |
  | 0.2661        | 1.73  | 750  | 0.2975          | 0.9133   |
  | 0.235         | 1.85  | 800  | 0.2692          | 0.92     |
  | 0.2182        | 1.96  | 850  | 0.3247          | 0.9067   |
  | 0.1762        | 2.08  | 900  | 0.3693          | 0.9133   |
  | 0.2086        | 2.19  | 950  | 0.4465          | 0.8933   |
  | 0.1444        | 2.31  | 1000 | 0.4225          | 0.9      |
  | 0.2228        | 2.42  | 1050 | 0.3794          | 0.9067   |
  | 0.1634        | 2.54  | 1100 | 0.4783          | 0.8933   |
  | 0.1561        | 2.66  | 1150 | 0.3476          | 0.9267   |
  | 0.1286        | 2.77  | 1200 | 0.5080          | 0.8933   |
  | 0.1647        | 2.89  | 1250 | 0.4369          | 0.9067   |
  | 0.1059        | 3.0   | 1300 | 0.4132          | 0.9133   |
  | 0.1069        | 3.12  | 1350 | 0.6070          | 0.8733   |
  | 0.108         | 3.23  | 1400 | 0.4909          | 0.9      |
  | 0.0741        | 3.35  | 1450 | 0.5231          | 0.9      |
  | 0.1204        | 3.46  | 1500 | 0.4517          | 0.9067   |
  | 0.106         | 3.58  | 1550 | 0.4685          | 0.8933   |
  | 0.1375        | 3.7   | 1600 | 0.4597          | 0.9067   |
  | 0.0727        | 3.81  | 1650 | 0.4443          | 0.9      |
  | 0.0669        | 3.93  | 1700 | 0.4324          | 0.9067   |
  | 0.081         | 4.04  | 1750 | 0.4176          | 0.9133   |
  | 0.0462        | 4.16  | 1800 | 0.4626          | 0.9133   |
  | 0.0382        | 4.27  | 1850 | 0.4732          | 0.9067   |
  | 0.0948        | 4.39  | 1900 | 0.5471          | 0.9      |
  | 0.0667        | 4.5   | 1950 | 0.5581          | 0.8867   |
  | 0.0878        | 4.62  | 2000 | 0.5429          | 0.8933   |
  | 0.0651        | 4.73  | 2050 | 0.5852          | 0.8933   |
  | 0.0492        | 4.85  | 2100 | 0.5793          | 0.8933   |
  | 0.0496        | 4.97  | 2150 | 0.5698          | 0.8933   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.13.0
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  