readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: stance_detection
    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. -->
  
  # stance_detection
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) towards 26 US SPAC stock mergers on Twitter.
  It achieves the following results on the evaluation set:
  - Loss: 0.4906
  - Accuracy: 0.8409
  - F1w: 0.8574
  - Acc0: 0.8293
  - Acc1: 0.6
  - Acc2: 0.7652
  - Acc3: 0.8637
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1w    | Acc0   | Acc1 | Acc2   | Acc3   |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:----:|:------:|:------:|
  | 0.7748        | 1.0   | 194  | 0.5172          | 0.8158   | 0.8297 | 0.8699 | 0.0  | 0.7429 | 0.8248 |
  | 0.5181        | 2.0   | 388  | 0.4692          | 0.8509   | 0.8587 | 0.8699 | 0.4  | 0.7429 | 0.8743 |
  | 0.3868        | 3.0   | 582  | 0.4906          | 0.8409   | 0.8574 | 0.8293 | 0.6  | 0.7652 | 0.8637 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.11.0
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  