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This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4144

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: 6e-06
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • total_eval_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • lr_scheduler_warmup_steps: 300
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
1.6699 0.02 20 1.5921
1.3657 0.04 40 1.5729
1.5918 0.07 60 1.5610
1.6343 0.09 80 1.5550
1.5015 0.11 100 1.5456
1.5233 0.13 120 1.5392
1.5025 0.15 140 1.5314
1.6424 0.18 160 1.5275
1.6267 0.2 180 1.5219
1.4698 0.22 200 1.5174
1.4297 0.24 220 1.5131
1.4826 0.26 240 1.5065
1.3671 0.29 260 1.4998
1.3661 0.31 280 1.4971
1.3012 0.33 300 1.4908
1.7249 0.35 320 1.4869
1.1596 0.37 340 1.4837
1.3188 0.4 360 1.4806
1.5087 0.42 380 1.4785
1.6028 0.44 400 1.4739
1.4167 0.46 420 1.4715
1.4823 0.48 440 1.4666
1.5418 0.51 460 1.4637
1.6369 0.53 480 1.4619
1.5098 0.55 500 1.4604
1.5404 0.57 520 1.4586
1.4594 0.6 540 1.4539
1.6358 0.62 560 1.4516
1.5025 0.64 580 1.4481
1.5119 0.66 600 1.4455
1.4617 0.68 620 1.4444
1.5281 0.71 640 1.4422
1.3506 0.73 660 1.4400
1.4467 0.75 680 1.4379
1.3382 0.77 700 1.4393
1.4894 0.79 720 1.4361
1.496 0.82 740 1.4329
1.516 0.84 760 1.4314
1.4118 0.86 780 1.4303
1.5408 0.88 800 1.4259
1.5307 0.9 820 1.4254
1.5376 0.93 840 1.4227
1.4129 0.95 860 1.4190
1.7808 0.97 880 1.4154
1.3279 0.99 900 1.4144

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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