readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: edos-2023-baseline-albert-base-v2-label_vector
    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. -->
  
  # edos-2023-baseline-albert-base-v2-label_vector
  
  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: 1.8762
  - F1: 0.1946
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 5
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.1002        | 1.18  | 100  | 1.9982          | 0.1023 |
  | 1.7832        | 2.35  | 200  | 1.8435          | 0.1310 |
  | 1.57          | 3.53  | 300  | 1.8097          | 0.1552 |
  | 1.3719        | 4.71  | 400  | 1.8216          | 0.1631 |
  | 1.2072        | 5.88  | 500  | 1.8138          | 0.1811 |
  | 1.0186        | 7.06  | 600  | 1.8762          | 0.1946 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  