V0503HMA6H / README.md
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metadata
license: mit
base_model: microsoft/phi-2
tags:
  - generated_from_trainer
model-index:
  - name: V0503HMA6H
    results: []

V0503HMA6H

This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0789

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine_with_restarts
  • lr_scheduler_warmup_steps: 80
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.6387 0.09 10 0.1732
0.1418 0.18 20 0.1123
0.1121 0.27 30 0.0965
0.1028 0.36 40 0.0867
0.0843 0.45 50 0.0755
0.0873 0.54 60 0.0846
0.0852 0.63 70 0.0728
0.0829 0.73 80 0.1861
1.6498 0.82 90 0.1034
2.9198 0.91 100 2.6894
4.4394 1.0 110 2.1642
1.1969 1.09 120 0.5102
0.4174 1.18 130 0.3222
0.3113 1.27 140 0.2990
0.2566 1.36 150 0.2072
0.1857 1.45 160 0.1786
0.1804 1.54 170 0.1617
0.1623 1.63 180 0.1588
0.1511 1.72 190 0.1394
0.1353 1.81 200 0.1214
0.1185 1.9 210 0.1228
0.1201 1.99 220 0.1079
0.1073 2.08 230 0.1116
0.1001 2.18 240 0.0929
0.0964 2.27 250 0.0884
0.0897 2.36 260 0.0858
0.0862 2.45 270 0.0836
0.0866 2.54 280 0.0830
0.086 2.63 290 0.0805
0.0818 2.72 300 0.0786
0.084 2.81 310 0.0774
0.0802 2.9 320 0.0790
0.0759 2.99 330 0.0789

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.14.1