readme: ---
  
  language: en        # <-- my language
  widget:
   - text: "Moody’s decision to upgrade the credit rating of Air Liquide is all the more remarkable as it is taking place in a more difficult macroeconomic and geopolitical environment. It underlines the Group’s capacity to maintain a high level of cash flow despite the fluctuations of the economy. Following Standard & Poor’s decision to upgrade Air Liquide’s credit rating, this decision recognizes the Group’s level of debt, which has been brought back to its pre-Airgas 2016 acquisition level in five years. It also reflects the largely demonstrated resilience of the Group’s business model."
   
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: roberta-sent-generali
    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. -->
  
  # roberta-sent-generali
  
  This model was fine-tuned on Roberta Large using a private dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4885
  - F1: 0.9104
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.355         | 1.0   | 262  | 0.3005          | 0.8829 |
  | 0.2201        | 2.0   | 524  | 0.3566          | 0.8930 |
  | 0.1293        | 3.0   | 786  | 0.3644          | 0.9193 |
  | 0.0662        | 4.0   | 1048 | 0.4202          | 0.9145 |
  | 0.026         | 5.0   | 1310 | 0.4885          | 0.9104 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  