readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy, F1 Score
  model-index:
  - name: distilbert-base-uncased-Financial_Sentiment_Analysis
    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-Finanacial_Sentiment_Analysis
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3079
  - Accuracy: 0.8529
  - F1 Score: 0.8564
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
  | 0.5569        | 1.0   | 134  | 0.3954          | 0.7591   | 0.7559   |
  | 0.3177        | 2.0   | 268  | 0.3391          | 0.8135   | 0.8151   |
  | 0.2479        | 3.0   | 402  | 0.3211          | 0.8322   | 0.8353   |
  | 0.2049        | 4.0   | 536  | 0.3066          | 0.8463   | 0.8506   |
  | 0.1802        | 5.0   | 670  | 0.3079          | 0.8529   | 0.8564   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  