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mistral_7b_cosine_lr_2e-4_bs2

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3819

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: 0.0002
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • lr_scheduler_warmup_steps: 15
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss
3.5854 0.0366 10 0.7044
0.6542 0.0732 20 0.8683
0.5736 0.1098 30 0.5023
0.4886 0.1465 40 0.4735
0.4757 0.1831 50 0.4552
0.453 0.2197 60 0.4451
0.4494 0.2563 70 0.4380
0.4457 0.2929 80 0.4329
0.4353 0.3295 90 0.4271
0.434 0.3661 100 0.4239
0.4307 0.4027 110 0.4198
0.4256 0.4394 120 0.4167
0.4173 0.4760 130 0.4130
0.4195 0.5126 140 0.4100
0.4159 0.5492 150 0.4075
0.4102 0.5858 160 0.4045
0.4135 0.6224 170 0.4034
0.408 0.6590 180 0.4004
0.405 0.6957 190 0.3992
0.4053 0.7323 200 0.3960
0.3994 0.7689 210 0.3934
0.3968 0.8055 220 0.3914
0.3966 0.8421 230 0.3885
0.3894 0.8787 240 0.3868
0.3896 0.9153 250 0.3860
0.3939 0.9519 260 0.3836
0.387 0.9886 270 0.3818
0.3511 1.0252 280 0.3839
0.3316 1.0618 290 0.3834
0.3281 1.0984 300 0.3819

Framework versions

  • PEFT 0.13.2
  • Transformers 4.45.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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