readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: bert-base-uncased-finetuned-GP-Sentiment
    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. -->
  
  # bert-base-uncased-finetuned-GP-Sentiment
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7815
  - F1: 0.6808
  - Accuracy: 0.7390
  
  ## 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: 2e-05
  - train_batch_size: 32
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
  | No log        | 1.0   | 313  | 0.7492          | 0.6448 | 0.6845   |
  | 0.7419        | 2.0   | 626  | 0.7281          | 0.6800 | 0.7350   |
  | 0.7419        | 3.0   | 939  | 0.7815          | 0.6808 | 0.7390   |
  | 0.5309        | 4.0   | 1252 | 0.8782          | 0.6799 | 0.7422   |
  | 0.336         | 5.0   | 1565 | 1.1222          | 0.6792 | 0.7390   |
  | 0.336         | 6.0   | 1878 | 1.1544          | 0.6671 | 0.7174   |
  | 0.219         | 7.0   | 2191 | 1.3721          | 0.6627 | 0.7246   |
  | 0.1541        | 8.0   | 2504 | 1.4864          | 0.6652 | 0.7326   |
  | 0.1541        | 9.0   | 2817 | 1.6475          | 0.6660 | 0.7446   |
  | 0.1094        | 10.0  | 3130 | 1.6749          | 0.6700 | 0.7446   |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  