twitter-roberta-base-sentiment-latest_12112024T150727

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: 1.3348
  • F1: 0.4579
  • 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 1.8285 0.1193 0.0000
No log 2.0 173 1.8031 0.3302 0.0000
No log 2.9942 259 1.5578 0.3690 0.0000
No log 4.0 346 1.4611 0.4092 0.0000
No log 4.9942 432 1.4700 0.4079 0.0000
1.3786 6.0 519 1.3348 0.4579 0.0000
1.3786 6.9942 605 1.6543 0.4193 1e-05
1.3786 8.0 692 1.4421 0.4858 1e-05
1.3786 8.9942 778 1.5573 0.4603 0.0000
1.3786 10.0 865 1.5451 0.4797 0.0000
1.3786 10.9942 951 1.8338 0.4396 0.0000
0.6407 12.0 1038 1.9383 0.4364 0.0000
0.6407 12.9942 1124 1.7573 0.4680 0.0000
0.6407 14.0 1211 1.8321 0.4735 0.0000
0.6407 14.9942 1297 1.9524 0.4619 0.0000
0.6407 16.0 1384 2.1822 0.4591 0.0000
0.6407 16.9942 1470 2.1302 0.4686 6e-06
0.2608 18.0 1557 2.5139 0.4467 0.0000
0.2608 18.9942 1643 2.3385 0.4641 0.0000
0.2608 20.0 1730 2.3281 0.4726 0.0000
0.2608 20.9942 1816 2.5489 0.4722 0.0000
0.2608 22.0 1903 2.5727 0.4745 0.0000
0.2608 22.9942 1989 2.5584 0.4694 0.0000
0.1026 24.0 2076 2.8115 0.4584 0.0000
0.1026 24.9942 2162 2.7270 0.4691 0.0000
0.1026 26.0 2249 2.7379 0.4746 7e-07
0.1026 26.9942 2335 2.8336 0.4757 4e-07
0.1026 28.0 2422 2.8201 0.4703 2e-07
0.057 28.9942 2508 2.8292 0.4691 0.0
0.057 29.8266 2580 2.8271 0.4691 0.0

Framework versions

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