readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - f1
  - recall
  model-index:
  - name: TwitchLeagueBert-1000k-finetuned-highlight-detection
    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. -->
  
  # TwitchLeagueBert-1000k-finetuned-highlight-detection
  
  This model is a fine-tuned version of [Epidot/TwitchLeagueBert-1000k](https://huggingface.co/Epidot/TwitchLeagueBert-1000k) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1146
  - Precision: 0.4420
  - F1: 0.3977
  - Recall: 0.3614
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 | F1     | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
  | 0.0205        | 1.04  | 20000 | 0.1119          | 0.4665    | 0.4689 | 0.4712 |
  | 0.0091        | 2.09  | 40000 | 0.1086          | 0.4803    | 0.4447 | 0.4139 |
  | 0.0062        | 3.13  | 60000 | 0.1172          | 0.4382    | 0.4192 | 0.4018 |
  | 0.0038        | 4.18  | 80000 | 0.1146          | 0.4420    | 0.3977 | 0.3614 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.7.1
  - Datasets 2.0.0
  - Tokenizers 0.12.1
  