readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: distilbert-cord-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. -->
  
  # distilbert-cord-ner
  
  This model is a fine-tuned version of [Geotrend/distilbert-base-en-fr-de-no-da-cased](https://huggingface.co/Geotrend/distilbert-base-en-fr-de-no-da-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1670
  - Precision: 0.9128
  - Recall: 0.9242
  - F1: 0.9185
  - Accuracy: 0.9656
  
  ## 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
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 113  | 0.1814          | 0.8480    | 0.8618 | 0.8548 | 0.9393   |
  | No log        | 2.0   | 226  | 0.1755          | 0.8669    | 0.9002 | 0.8832 | 0.9427   |
  | No log        | 3.0   | 339  | 0.1499          | 0.8800    | 0.8935 | 0.8867 | 0.9533   |
  | No log        | 4.0   | 452  | 0.1340          | 0.8975    | 0.9079 | 0.9027 | 0.9596   |
  | 0.1812        | 5.0   | 565  | 0.1553          | 0.8999    | 0.9146 | 0.9072 | 0.9592   |
  | 0.1812        | 6.0   | 678  | 0.1474          | 0.8961    | 0.9021 | 0.8991 | 0.9562   |
  | 0.1812        | 7.0   | 791  | 0.1682          | 0.9135    | 0.9223 | 0.9179 | 0.9622   |
  | 0.1812        | 8.0   | 904  | 0.1663          | 0.8960    | 0.9175 | 0.9066 | 0.9613   |
  | 0.0199        | 9.0   | 1017 | 0.1753          | 0.9061    | 0.9261 | 0.9160 | 0.9635   |
  | 0.0199        | 10.0  | 1130 | 0.1670          | 0.9128    | 0.9242 | 0.9185 | 0.9656   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  