readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - cynthiachan/FeedRef_10pct
  model-index:
  - name: training
    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. -->
  
  # training
  
  This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the cynthiachan/FeedRef_10pct dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0810
  - Attackid Precision: 1.0
  - Attackid Recall: 1.0
  - Attackid F1: 1.0
  - Attackid Number: 6
  - Cve Precision: 1.0
  - Cve Recall: 1.0
  - Cve F1: 1.0
  - Cve Number: 11
  - Defenderthreat Precision: 0.0
  - Defenderthreat Recall: 0.0
  - Defenderthreat F1: 0.0
  - Defenderthreat Number: 2
  - Domain Precision: 1.0
  - Domain Recall: 0.9565
  - Domain F1: 0.9778
  - Domain Number: 23
  - Email Precision: 1.0
  - Email Recall: 1.0
  - Email F1: 1.0
  - Email Number: 3
  - Filepath Precision: 0.8841
  - Filepath Recall: 0.8788
  - Filepath F1: 0.8815
  - Filepath Number: 165
  - Hostname Precision: 1.0
  - Hostname Recall: 1.0
  - Hostname F1: 1.0
  - Hostname Number: 12
  - Ipv4 Precision: 1.0
  - Ipv4 Recall: 1.0
  - Ipv4 F1: 1.0
  - Ipv4 Number: 12
  - Md5 Precision: 0.8333
  - Md5 Recall: 0.9615
  - Md5 F1: 0.8929
  - Md5 Number: 52
  - Sha1 Precision: 0.6667
  - Sha1 Recall: 0.8571
  - Sha1 F1: 0.75
  - Sha1 Number: 7
  - Sha256 Precision: 0.9565
  - Sha256 Recall: 1.0
  - Sha256 F1: 0.9778
  - Sha256 Number: 44
  - Uri Precision: 0.0
  - Uri Recall: 0.0
  - Uri F1: 0.0
  - Uri Number: 1
  - Overall Precision: 0.9014
  - Overall Recall: 0.9201
  - Overall F1: 0.9107
  - Overall Accuracy: 0.9851
  
  ## 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: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Attackid Precision | Attackid Recall | Attackid F1 | Attackid Number | Cve Precision | Cve Recall | Cve F1 | Cve Number | Defenderthreat Precision | Defenderthreat Recall | Defenderthreat F1 | Defenderthreat Number | Domain Precision | Domain Recall | Domain F1 | Domain Number | Email Precision | Email Recall | Email F1 | Email Number | Filepath Precision | Filepath Recall | Filepath F1 | Filepath Number | Hostname Precision | Hostname Recall | Hostname F1 | Hostname Number | Ipv4 Precision | Ipv4 Recall | Ipv4 F1 | Ipv4 Number | Md5 Precision | Md5 Recall | Md5 F1 | Md5 Number | Sha1 Precision | Sha1 Recall | Sha1 F1 | Sha1 Number | Sha256 Precision | Sha256 Recall | Sha256 F1 | Sha256 Number | Uri Precision | Uri Recall | Uri F1 | Uri Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:-------------:|:----------:|:------:|:----------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:----------------:|:-------------:|:---------:|:-------------:|:---------------:|:------------:|:--------:|:------------:|:------------------:|:---------------:|:-----------:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------:|:----------:|:------:|:----------:|:--------------:|:-----------:|:-------:|:-----------:|:----------------:|:-------------:|:---------:|:-------------:|:-------------:|:----------:|:------:|:----------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 0.3797        | 0.37  | 500  | 0.1998          | 0.0                | 0.0             | 0.0         | 6               | 0.0           | 0.0        | 0.0    | 11         | 0.0                      | 0.0                   | 0.0               | 2                     | 0.0286           | 0.0435        | 0.0345    | 23            | 0.0             | 0.0          | 0.0      | 3            | 0.5108             | 0.7152          | 0.5960      | 165             | 0.1774             | 0.9167          | 0.2973      | 12              | 0.4            | 0.5         | 0.4444  | 12          | 0.3194        | 0.4423     | 0.3710 | 52         | 0.0            | 0.0         | 0.0     | 7           | 0.4588           | 0.8864        | 0.6047    | 44            | 0.0           | 0.0        | 0.0    | 1          | 0.3875            | 0.5858         | 0.4664     | 0.9593           |
  | 0.1713        | 0.75  | 1000 | 0.1619          | 0.6                | 0.5             | 0.5455      | 6               | 0.5           | 0.6364     | 0.56   | 11         | 0.0                      | 0.0              