readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: rlt_2409_1450
    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. -->
  
  # rlt_2409_1450
  
  This model is a fine-tuned version of [svalabs/gbert-large-zeroshot-nli](https://huggingface.co/svalabs/gbert-large-zeroshot-nli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0518
  - F1: 0.9826
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 0.99  | 36   | 0.5165          | 0.8542 |
  | No log        | 1.99  | 72   | 0.1459          | 0.9599 |
  | No log        | 2.99  | 108  | 0.0733          | 0.9882 |
  | No log        | 3.99  | 144  | 0.1385          | 0.9502 |
  | No log        | 4.99  | 180  | 0.0948          | 0.9806 |
  | No log        | 5.99  | 216  | 0.0699          | 0.9822 |
  | No log        | 6.99  | 252  | 0.0582          | 0.9859 |
  | No log        | 7.99  | 288  | 0.0340          | 0.9933 |
  | No log        | 8.99  | 324  | 0.0475          | 0.9826 |
  | No log        | 9.99  | 360  | 0.0518          | 0.9826 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  