dianamihalache27's picture
End of training
040ed98 verified
|
raw
history blame
2.87 kB
metadata
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: Twroberta-baseB_15epoch
    results: []

Twroberta-baseB_15epoch

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-irony on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1971
  • Accuracy: 0.7686
  • Precision: 0.2328
  • Recall: 0.3210
  • F1: 0.2693

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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
No log 1.0 217 0.1248 0.8571 0.0 0.0 0.0
No log 2.0 434 0.1250 0.8679 0.5258 0.0701 0.1237
0.1617 3.0 651 0.1225 0.825 0.2771 0.2657 0.2712
0.1617 4.0 868 0.1325 0.8079 0.3164 0.2583 0.2554
0.0885 5.0 1085 0.1553 0.7707 0.2169 0.2694 0.2391
0.0885 6.0 1302 0.1680 0.7507 0.2112 0.3358 0.2592
0.0392 7.0 1519 0.2129 0.7093 0.1936 0.3875 0.2575
0.0392 8.0 1736 0.1717 0.7764 0.2316 0.2841 0.2528
0.0392 9.0 1953 0.1915 0.7507 0.2287 0.3321 0.2671
0.0178 10.0 2170 0.1987 0.7586 0.2294 0.3653 0.2809
0.0178 11.0 2387 0.1923 0.7564 0.2287 0.3358 0.2710
0.0108 12.0 2604 0.1925 0.7586 0.2317 0.3358 0.2729
0.0108 13.0 2821 0.1965 0.775 0.2356 0.3284 0.2743
0.0078 14.0 3038 0.1964 0.7621 0.2326 0.3284 0.2712
0.0078 15.0 3255 0.1971 0.7686 0.2328 0.3210 0.2693

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1