readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: deberta-finetuned-ner-finetuned-ner
    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. -->
  
  # deberta-finetuned-ner-finetuned-ner
  
  This model is a fine-tuned version of [baptiste/deberta-finetuned-ner](https://huggingface.co/baptiste/deberta-finetuned-ner) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7964
  - Precision: 0.6210
  - Recall: 0.3188
  - F1: 0.4213
  - Accuracy: 0.8212
  
  ## 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: 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 4    | 1.0763          | 0.5583    | 0.1387 | 0.2222 | 0.7916   |
  | No log        | 2.0   | 8    | 0.8910          | 0.8108    | 0.3106 | 0.4491 | 0.8212   |
  | No log        | 3.0   | 12   | 0.7964          | 0.6210    | 0.3188 | 0.4213 | 0.8212   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  