readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-bert-base-multilingual-uncased-hindi-only-memes
    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-data-bert-base-multilingual-uncased-hindi-only-memes
  
  This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5614
  - Accuracy: 0.9031
  - Precision: 0.9064
  - Recall: 0.9057
  - F1: 0.9060
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.5408        | 1.0   | 511  | 0.4798          | 0.7974   | 0.8447    | 0.8049 | 0.7940 |
  | 0.3117        | 2.0   | 1022 | 0.3576          | 0.8844   | 0.8875    | 0.8882 | 0.8869 |
  | 0.2019        | 3.0   | 1533 | 0.3401          | 0.9020   | 0.9076    | 0.9047 | 0.9052 |
  | 0.1364        | 4.0   | 2044 | 0.4519          | 0.8888   | 0.8936    | 0.8921 | 0.8923 |
  | 0.0767        | 5.0   | 2555 | 0.5251          | 0.8987   | 0.9024    | 0.9016 | 0.9019 |
  | 0.0433        | 6.0   | 3066 | 0.5614          | 0.9031   | 0.9064    | 0.9057 | 0.9060 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  