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biden_stance_detection
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metadata
library_name: peft
tags:
  - generated_from_trainer
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: twitter-roberta-base-sentiment-latest-biden-stance-1
    results: []

twitter-roberta-base-sentiment-latest-biden-stance-1

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

  • Loss: 1.4037
  • Accuracy: {'accuracy': 0.5688073394495413}
  • Precision: {'precision': 0.5540838852097131}
  • Recall: {'recall': 0.6640211640211641}
  • F1 Score: {'f1': 0.6040914560770156}

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: 0.001
  • train_batch_size: 4
  • eval_batch_size: 4
  • 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 Accuracy Precision Recall F1 Score
0.4339 1.0 3600 0.4173 {'accuracy': 0.8925} {'precision': 0.857630979498861} {'recall': 0.94125} {'f1': 0.8974970202622169}
0.3848 2.0 7200 0.5757 {'accuracy': 0.854375} {'precision': 0.9341500765696784} {'recall': 0.7625} {'f1': 0.8396421197522368}
0.4094 3.0 10800 0.3543 {'accuracy': 0.904375} {'precision': 0.8655367231638418} {'recall': 0.9575} {'f1': 0.9091988130563798}
0.3937 4.0 14400 0.2576 {'accuracy': 0.91125} {'precision': 0.9092039800995025} {'recall': 0.91375} {'f1': 0.9114713216957606}
0.3401 5.0 18000 0.2671 {'accuracy': 0.91625} {'precision': 0.9291237113402062} {'recall': 0.90125} {'f1': 0.9149746192893401}
0.352 6.0 21600 0.2429 {'accuracy': 0.91875} {'precision': 0.9294871794871795} {'recall': 0.90625} {'f1': 0.9177215189873418}
0.2883 7.0 25200 0.2857 {'accuracy': 0.915625} {'precision': 0.917189460476788} {'recall': 0.91375} {'f1': 0.915466499686913}
0.2894 8.0 28800 0.2270 {'accuracy': 0.92375} {'precision': 0.9302030456852792} {'recall': 0.91625} {'f1': 0.9231738035264484}
0.282 9.0 32400 0.2518 {'accuracy': 0.92} {'precision': 0.9189526184538653} {'recall': 0.92125} {'f1': 0.920099875156055}
0.2485 10.0 36000 0.2351 {'accuracy': 0.92375} {'precision': 0.9269521410579346} {'recall': 0.92} {'f1': 0.9234629861982434}

Framework versions

  • PEFT 0.10.0
  • Transformers 4.38.2
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2