readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: roberta-large-finetuned-chunking
    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-large-finetuned-chunking
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4192
  - Precision: 0.3222
  - Recall: 0.3161
  - F1: 0.3191
  - Accuracy: 0.8632
  
  ## 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: 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: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0373        | 1.0   | 2498  | 0.9545          | 0.3166    | 0.2545 | 0.2822 | 0.8656   |
  | 0.0045        | 2.0   | 4996  | 1.1324          | 0.2667    | 0.3142 | 0.2885 | 0.8525   |
  | 0.0022        | 3.0   | 7494  | 1.3138          | 0.3349    | 0.3097 | 0.3218 | 0.8672   |
  | 0.0015        | 4.0   | 9992  | 1.3454          | 0.3261    | 0.3260 | 0.3260 | 0.8647   |
  | 0.0014        | 5.0   | 12490 | 1.3640          | 0.3064    | 0.3126 | 0.3095 | 0.8603   |
  | 0.0008        | 6.0   | 14988 | 1.4192          | 0.3222    | 0.3161 | 0.3191 | 0.8632   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  