readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: SST2_DistilBERT_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_DistilBERT_5E
  
  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: 0.4125
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6744        | 0.12  | 50   | 0.6094          | 0.66     |
  | 0.4942        | 0.23  | 100  | 0.3772          | 0.8667   |
  | 0.3857        | 0.35  | 150  | 0.3256          | 0.8867   |
  | 0.3483        | 0.46  | 200  | 0.3634          | 0.84     |
  | 0.3235        | 0.58  | 250  | 0.3338          | 0.8733   |
  | 0.3129        | 0.69  | 300  | 0.3482          | 0.8667   |
  | 0.3573        | 0.81  | 350  | 0.3632          | 0.8333   |
  | 0.3266        | 0.92  | 400  | 0.3274          | 0.86     |
  | 0.2615        | 1.04  | 450  | 0.3400          | 0.8667   |
  | 0.2409        | 1.15  | 500  | 0.3541          | 0.8467   |
  | 0.2508        | 1.27  | 550  | 0.2997          | 0.88     |
  | 0.2442        | 1.39  | 600  | 0.3654          | 0.86     |
  | 0.2625        | 1.5   | 650  | 0.3302          | 0.8667   |
  | 0.1983        | 1.62  | 700  | 0.3184          | 0.8867   |
  | 0.2356        | 1.73  | 750  | 0.3239          | 0.8867   |
  | 0.2078        | 1.85  | 800  | 0.2968          | 0.9      |
  | 0.2343        | 1.96  | 850  | 0.3148          | 0.8933   |
  | 0.1544        | 2.08  | 900  | 0.3535          | 0.9      |
  | 0.1407        | 2.19  | 950  | 0.3603          | 0.8733   |
  | 0.187         | 2.31  | 1000 | 0.3843          | 0.88     |
  | 0.144         | 2.42  | 1050 | 0.4546          | 0.8467   |
  | 0.1786        | 2.54  | 1100 | 0.3681          | 0.88     |
  | 0.1315        | 2.66  | 1150 | 0.3806          | 0.8867   |
  | 0.1399        | 2.77  | 1200 | 0.3880          | 0.8867   |
  | 0.1905        | 2.89  | 1250 | 0.3944          | 0.8733   |
  | 0.2043        | 3.0   | 1300 | 0.3974          | 0.8733   |
  | 0.1081        | 3.12  | 1350 | 0.3731          | 0.9067   |
  | 0.1055        | 3.23  | 1400 | 0.3809          | 0.8867   |
  | 0.1092        | 3.35  | 1450 | 0.3568          | 0.9      |
  | 0.0981        | 3.46  | 1500 | 0.3610          | 0.9133   |
  | 0.109         | 3.58  | 1550 | 0.4126          | 0.8867   |
  | 0.1001        | 3.7   | 1600 | 0.3831          | 0.9      |
  | 0.1027        | 3.81  | 1650 | 0.4064          | 0.9      |
  | 0.133         | 3.93  | 1700 | 0.3845          | 0.9      |
  | 0.1031        | 4.04  | 1750 | 0.3915          | 0.9      |
  | 0.0772        | 4.16  | 1800 | 0.3988          | 0.8867   |
  | 0.0785        | 4.27  | 1850 | 0.3962          | 0.9      |
  | 0.1059        | 4.39  | 1900 | 0.3969          | 0.9      |
  | 0.0668        | 4.5   | 1950 | 0.4095          | 0.8933   |
  | 0.0915        | 4.62  | 2000 | 0.4077          | 0.8933   |
  | 0.1413        | 4.73  | 2050 | 0.4004          | 0.9067   |
  | 0.0727        | 4.85  | 2100 | 0.4100          | 0.8933   |
  | 0.0724        | 4.97  | 2150 | 0.4125          | 0.8933   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  