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t5-base-pointer-cstop_artificial

This model is a fine-tuned version of google/mt5-base on the cstop_artificial dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0776
  • Exact Match: 0.7746

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 64
  • total_train_batch_size: 512
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 3000

Training results

Training Loss Epoch Step Validation Loss Exact Match
1.7482 28.5 200 0.2505 0.1020
0.1366 57.13 400 0.0776 0.3238
0.0275 85.63 600 0.0881 0.3381
0.0114 114.25 800 0.0990 0.3399
0.0064 142.75 1000 0.1120 0.3417
0.0045 171.38 1200 0.1081 0.3435
0.0036 199.88 1400 0.1230 0.3435
0.0025 228.5 1600 0.1211 0.3399
0.002 257.13 1800 0.1367 0.3399
0.0016 285.63 2000 0.1324 0.3435
0.0013 314.25 2200 0.1340 0.3470
0.001 342.75 2400 0.1374 0.3435
0.0009 371.38 2600 0.1384 0.3417
0.0007 399.88 2800 0.1422 0.3435
0.0006 428.5 3000 0.1452 0.3417

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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