distilbert-base-uncased-finetuned-sst-2-english_08112024T110433

This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4561
  • F1: 0.8591
  • 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: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Rate
No log 0.9942 86 1.8025 0.1776 0.0000
No log 2.0 173 1.7296 0.1902 0.0000
No log 2.9942 259 1.6400 0.3649 0.0000
No log 4.0 346 1.4873 0.4157 0.0000
No log 4.9942 432 1.2812 0.5119 0.0000
1.5846 6.0 519 1.0792 0.5668 0.0000
1.5846 6.9942 605 0.9450 0.6226 1e-05
1.5846 8.0 692 0.8238 0.6836 0.0000
1.5846 8.9942 778 0.7274 0.7374 0.0000
1.5846 10.0 865 0.6411 0.7734 0.0000
1.5846 10.9942 951 0.6020 0.7822 0.0000
0.7489 12.0 1038 0.5470 0.8157 0.0000
0.7489 12.9942 1124 0.5161 0.8299 0.0000
0.7489 14.0 1211 0.4952 0.8454 0.0000
0.7489 14.9942 1297 0.4768 0.8518 0.0000
0.7489 16.0 1384 0.4664 0.8546 0.0000
0.7489 16.9942 1470 0.4665 0.8565 0.0000
0.3329 18.0 1557 0.4561 0.8591 5e-07
0.3329 18.9942 1643 0.4578 0.8585 1e-07
0.3329 19.8844 1720 0.4579 0.8584 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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