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twitter-roberta-base-sentiment-latest_12112024T120259

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metadata
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: twitter-roberta-base-sentiment-latest_12112024T120259
    results: []

twitter-roberta-base-sentiment-latest_12112024T120259

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

  • Loss: 0.4912
  • F1: 0.8803
  • Learning Rate: 0.0

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 600
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Rate
No log 0.9942 86 1.7812 0.1230 0.0000
No log 2.0 173 1.6480 0.3596 0.0000
No log 2.9942 259 1.3462 0.4748 0.0000
No log 4.0 346 1.1145 0.5480 0.0000
No log 4.9942 432 0.9935 0.5877 0.0000
1.3977 6.0 519 0.9023 0.6390 0.0000
1.3977 6.9942 605 0.8538 0.6798 1e-05
1.3977 8.0 692 0.7381 0.7388 1e-05
1.3977 8.9942 778 0.6558 0.7696 0.0000
1.3977 10.0 865 0.6072 0.7963 0.0000
1.3977 10.9942 951 0.5771 0.8139 0.0000
0.6178 12.0 1038 0.5692 0.8270 0.0000
0.6178 12.9942 1124 0.5208 0.8513 0.0000
0.6178 14.0 1211 0.5416 0.8487 0.0000
0.6178 14.9942 1297 0.5073 0.8655 0.0000
0.6178 16.0 1384 0.5052 0.8740 0.0000
0.6178 16.9942 1470 0.4912 0.8803 6e-06
0.2205 18.0 1557 0.5557 0.8700 0.0000
0.2205 18.9942 1643 0.5021 0.8845 0.0000
0.2205 20.0 1730 0.5382 0.8837 0.0000
0.2205 20.9942 1816 0.6147 0.8730 0.0000
0.2205 22.0 1903 0.5978 0.8762 0.0000
0.2205 22.9942 1989 0.6037 0.8756 0.0000
0.0833 24.0 2076 0.6226 0.8755 0.0000
0.0833 24.9942 2162 0.6136 0.8777 0.0000
0.0833 26.0 2249 0.5938 0.8815 7e-07
0.0833 26.9942 2335 0.6318 0.8766 4e-07
0.0833 28.0 2422 0.6302 0.8783 2e-07
0.0462 28.9942 2508 0.6325 0.8777 0.0
0.0462 29.8266 2580 0.6322 0.8777 0.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.19.1