CodeIsAbstract's picture
Model save
88c7aeb verified
|
Raw
History Blame Contribute Delete
4.55 kB
metadata
library_name: transformers
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: HybridModelScratch_lightn_Conti
    results: []

HybridModelScratch_lightn_Conti

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

  • Loss: 3.2749
  • Accuracy: 0.3848

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: 120
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 150
  • training_steps: 50000

Training results

Training Loss Epoch Step Accuracy Validation Loss
4.5799 0.02 1000 0.2697 4.5051
4.1703 0.04 2000 0.3056 4.1036
4.0044 0.06 3000 0.3195 3.9451
3.8638 0.08 4000 0.3281 3.8499
3.7991 0.1 5000 0.3350 3.7702
3.6996 0.12 6000 0.3414 3.7112
3.6319 0.14 7000 0.3448 3.6666
3.6062 0.16 8000 0.3476 3.6405
3.6643 0.18 9000 0.3498 3.6175
3.5992 0.2 10000 0.3535 3.5797
3.5671 0.22 11000 0.3559 3.5543
3.5230 0.24 12000 0.3578 3.5308
3.5930 0.26 13000 0.3593 3.5190
3.5475 0.28 14000 0.3616 3.4961
3.5220 0.3 15000 0.3633 3.4778
3.5050 0.32 16000 0.3644 3.4654
3.4776 0.34 17000 0.3666 3.4458
3.4829 0.36 18000 0.3674 3.4346
3.4483 0.38 19000 0.3694 3.4189
3.4418 0.4 20000 0.3704 3.4063
3.4183 0.42 21000 0.3720 3.3956
3.3858 0.44 22000 0.3725 3.3870
3.3654 0.46 23000 0.3728 3.3824
3.3943 0.48 24000 0.3734 3.3756
3.3957 0.5 25000 0.3757 3.3548
3.3787 0.52 26000 0.3769 3.3452
3.3605 0.54 27000 0.3777 3.3393
3.3707 0.56 28000 0.3787 3.3302
3.3508 0.58 29000 0.3793 3.3221
3.3566 0.6 30000 0.3802 3.3148
3.3441 0.62 31000 0.3809 3.3054
3.3268 0.64 32000 0.3814 3.3028
3.0620 0.02 33000 3.3109 0.3804
3.0159 0.04 34000 3.3074 0.3810
3.0230 0.06 35000 3.3025 0.3815
3.0335 0.08 36000 3.2988 0.3821
3.0098 0.1 37000 3.2959 0.3826
3.0096 0.12 38000 3.2932 0.3826
2.9760 0.14 39000 3.2904 0.3831
2.9701 0.16 40000 3.2869 0.3832
2.9654 0.18 41000 3.2847 0.3837
2.9752 0.2 42000 3.2823 0.3839
2.9480 0.22 43000 3.2810 0.3840
2.9637 0.24 44000 3.2790 0.3842
2.9721 0.26 45000 3.2772 0.3843
2.9694 0.28 46000 3.2765 0.3847
2.9577 0.3 47000 3.2756 0.3847
2.9573 0.32 48000 3.2751 0.3847
2.9537 0.34 49000 3.2749 0.3848
2.9677 0.36 50000 3.2749 0.3848

Framework versions

  • Transformers 5.13.0
  • Pytorch 2.8.0+cu128
  • Datasets 5.0.0
  • Tokenizers 0.22.2