callmesan's picture
End of training
614fed1 verified
metadata
library_name: transformers
license: mit
base_model: cardiffnlp/twitter-roberta-large-hate-latest
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: twitter-roberta-large-hate-latest-hinglish-binary
    results: []

twitter-roberta-large-hate-latest-hinglish-binary

This model is a fine-tuned version of cardiffnlp/twitter-roberta-large-hate-latest on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8288
  • Accuracy: 0.6779
  • Precision: 0.6455
  • Recall: 0.6188
  • F1: 0.6218

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: 32
  • eval_batch_size: 128
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • 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 Accuracy Precision Recall F1
0.6392 0.9709 25 0.6656 0.6376 0.3188 0.5 0.3894
0.63 1.9806 51 0.7095 0.6403 0.8197 0.5038 0.3975
0.6117 2.9903 77 0.6043 0.6921 0.6720 0.6174 0.6176
0.5974 4.0 103 0.6540 0.6730 0.6787 0.5667 0.5369
0.5512 4.9709 128 0.6216 0.6948 0.6745 0.6228 0.6243
0.5162 5.9806 154 0.6164 0.7057 0.6873 0.6394 0.6438
0.4525 6.9903 180 0.6715 0.6948 0.6757 0.6211 0.6221
0.4207 8.0 206 0.7581 0.7084 0.6844 0.6562 0.6620
0.3381 8.9709 231 0.7439 0.6812 0.6560 0.6575 0.6567
0.3016 9.7087 250 0.7481 0.7030 0.6762 0.6649 0.6688

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0