readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-sentiment-reddit-crypto
    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. -->
  
  # distilbert-base-uncased-sentiment-reddit-crypto
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the crypto-related reddit comments dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3070
  - Accuracy: 0.8915
  
  Accuracy on the final test set was: 0.8641
  
  ## Training and evaluation data
  
  Training and validation data collected from 2 sources:
  
  1. [Kaggle reddit cryptocurrency posts and comments](https://www.kaggle.com/datasets/gpreda/reddit-cryptocurrency)
  2. [Kaggle reddit cryptocurrency related posts from various subreddits](https://www.kaggle.com/datasets/leukipp/reddit-crypto-data). Comments from subreddits: `'cryptocurrency', 'bitcoin', 'ethereum', 'dogecoin'` were extracted.
  
  Final test data source is from https://www.surgehq.ai/datasets/crypto-sentiment-dataset.
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.2823        | 1.0   | 5109  | 0.2658          | 0.8840   |
  | 0.1905        | 2.0   | 10218 | 0.3070          | 0.8915   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  