readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: umberto-commoncrawl-cased-v1-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. -->
  
  # umberto-commoncrawl-cased-v1-finetuned-ner
  
  This model is a fine-tuned version of [Musixmatch/umberto-commoncrawl-cased-v1](https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6238
  - Precision: 0.2697
  - Recall: 0.2449
  - F1: 0.2567
  - Accuracy: 0.9356
  
  ## 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: 5
  - eval_batch_size: 5
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1000
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0    | 12    | 3.1383          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 2.0    | 24    | 2.2233          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 3.0    | 36    | 1.9234          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 4.0    | 48    | 1.7967          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 5.0    | 60    | 1.7242          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 6.0    | 72    | 1.6597          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 7.0    | 84    | 1.6039          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 8.0    | 96    | 1.5455          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 9.0    | 108   | 1.4896          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 10.0   | 120   | 1.4305          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 11.0   | 132   | 1.3792          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 12.0   | 144   | 1.3254          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 13.0   | 156   | 1.2737          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 14.0   | 168   | 1.2242          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 15.0   | 180   | 1.1752          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 16.0   | 192   | 1.1266          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 17.0   | 204   | 1.0792          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 18.0   | 216   | 1.0360          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 19.0   | 228   | 0.9927          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 20.0   | 240   | 0.9501          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 21.0   | 252   | 0.9097          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 22.0   | 264   | 0.8717          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 23.0   | 276   | 0.8344          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 24.0   | 288   | 0.7995          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 25.0   | 300   | 0.7663          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 26.0   | 312   | 0.7398          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 27.0   | 324   | 0.7077          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 28.0   | 336   | 0.6794          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 29.0   | 348   | 0.6531          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 30.0   | 360   | 0.6284          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 31.0   | 372   | 0.6053          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 32.0   | 384   | 0.5838          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 33.0   | 396   | 0.5635          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 34.0   | 408   | 0.5457          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 35.0   | 420   | 0.5285          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 36.0   | 432   | 0.5126          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 37.0   | 444   | 0.4990          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 38.0   | 456   | 0.4865          | 0.0       | 0.0    | 0.0    | 0.9420   |
  | No log        | 39.0   | 468   | 0.4757          | 0.