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sst-t5-base

This model is a fine-tuned version of t5-base on the sst dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0185
  • Mse: 0.0185

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 32
  • 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: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Mse
No log 1.0 267 0.0196 0.0196
0.0237 2.0 534 0.0179 0.0179
0.0237 3.0 801 0.0174 0.0174
0.0133 4.0 1068 0.0182 0.0182
0.0133 5.0 1335 0.0181 0.0181
0.0101 6.0 1602 0.0180 0.0180
0.0101 7.0 1869 0.0183 0.0183
0.0083 8.0 2136 0.0188 0.0188
0.0083 9.0 2403 0.0185 0.0186
0.0067 10.0 2670 0.0187 0.0187
0.0067 11.0 2937 0.0184 0.0184
0.0057 12.0 3204 0.0186 0.0186
0.0057 13.0 3471 0.0194 0.0194
0.005 14.0 3738 0.0175 0.0176
0.0045 15.0 4005 0.0182 0.0182
0.0045 16.0 4272 0.0183 0.0183
0.0041 17.0 4539 0.0187 0.0187
0.0041 18.0 4806 0.0186 0.0186
0.0038 19.0 5073 0.0188 0.0188
0.0038 20.0 5340 0.0185 0.0185

Framework versions

  • Transformers 4.37.0
  • Pytorch 1.13.1+cu117
  • Datasets 2.15.0
  • Tokenizers 0.15.2
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Dataset used to train kennethge123/sst-t5-base