readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: twitter_RoBERTa_token_itr0_1e-05_all_01_03_2022-15_02_39
    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. -->
  
  # twitter_RoBERTa_token_itr0_1e-05_all_01_03_2022-15_02_39
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2903
  - Precision: 0.2440
  - Recall: 0.4465
  - F1: 0.3155
  - Accuracy: 0.8706
  
  ## 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: 1e-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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 30   | 0.4378          | 0.0463    | 0.1136 | 0.0658 | 0.7742   |
  | No log        | 2.0   | 60   | 0.3739          | 0.1472    | 0.3756 | 0.2115 | 0.8284   |
  | No log        | 3.0   | 90   | 0.3422          | 0.1865    | 0.4330 | 0.2607 | 0.8374   |
  | No log        | 4.0   | 120  | 0.3286          | 0.2243    | 0.4833 | 0.3064 | 0.8438   |
  | No log        | 5.0   | 150  | 0.3239          | 0.2356    | 0.4809 | 0.3163 | 0.8490   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  