readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: albert-base-v2-finetuned-TRAC-DS
    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. -->
  
  # albert-base-v2-finetuned-TRAC-DS
  
  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: 0.8271
  - Accuracy: 0.6315
  - Precision: 0.6206
  - Recall: 0.6201
  - F1: 0.6147
  
  ## 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: 5.919508251872584e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0373        | 1.0   | 612  | 1.1241          | 0.3627   | 0.5914    | 0.3618 | 0.2414 |
  | 1.0617        | 2.0   | 1224 | 1.1039          | 0.3350   | 0.2781    | 0.3354 | 0.1740 |
  | 0.9791        | 3.0   | 1836 | 0.8365          | 0.5989   | 0.6192    | 0.5887 | 0.5883 |
  | 0.798         | 3.99  | 2448 | 0.8271          | 0.6315   | 0.6206    | 0.6201 | 0.6147 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  