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finetuned_mistral_on_ads

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

  • Loss: 1.5249

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
3.7417 0.0444 2 3.6685
3.6314 0.0889 4 3.2304
3.0686 0.1333 6 2.8771
2.5057 0.1778 8 2.7170
2.5453 0.2222 10 2.5886
2.5759 0.2667 12 2.4625
2.4252 0.3111 14 2.3477
2.4227 0.3556 16 2.2455
1.987 0.4 18 2.1370
2.0229 0.4444 20 2.0484
2.0755 0.4889 22 1.9746
1.9004 0.5333 24 1.9032
1.9381 0.5778 26 1.8405
1.7879 0.6222 28 1.7911
1.7544 0.6667 30 1.7584
1.7485 0.7111 32 1.7290
1.6927 0.7556 34 1.7030
1.8931 0.8 36 1.6825
1.5624 0.8444 38 1.6656
1.7061 0.8889 40 1.6528
1.7288 0.9333 42 1.6426
1.7839 0.9778 44 1.6347
1.5954 1.0222 46 1.6270
1.4288 1.0667 48 1.6177
1.5201 1.1111 50 1.6094
1.5281 1.1556 52 1.6037
1.4132 1.2 54 1.5998
1.4271 1.2444 56 1.5976
1.4778 1.2889 58 1.5952
1.5138 1.3333 60 1.5921
1.4539 1.3778 62 1.5875
1.4293 1.4222 64 1.5823
1.3673 1.4667 66 1.5773
1.5272 1.5111 68 1.5734
1.506 1.5556 70 1.5701
1.2929 1.6 72 1.5669
1.387 1.6444 74 1.5637
1.3375 1.6889 76 1.5609
1.4666 1.7333 78 1.5586
1.2295 1.7778 80 1.5553
1.5195 1.8222 82 1.5521
1.5116 1.8667 84 1.5488
1.2947 1.9111 86 1.5449
1.4651 1.9556 88 1.5399
1.5171 2.0 90 1.5351
1.1823 2.0444 92 1.5312
1.3729 2.0889 94 1.5286
1.2607 2.1333 96 1.5256
1.2048 2.1778 98 1.5237
1.2862 2.2222 100 1.5229
1.2584 2.2667 102 1.5224
1.2285 2.3111 104 1.5223
1.2794 2.3556 106 1.5222
1.2196 2.4 108 1.5227
1.2526 2.4444 110 1.5232
1.2876 2.4889 112 1.5237
1.1812 2.5333 114 1.5247
1.3622 2.5778 116 1.5255
1.229 2.6222 118 1.5261
1.2796 2.6667 120 1.5262
1.2059 2.7111 122 1.5258
1.3327 2.7556 124 1.5257
1.254 2.8 126 1.5257
1.2183 2.8444 128 1.5256
1.1979 2.8889 130 1.5254
1.2558 2.9333 132 1.5251
1.1405 2.9778 134 1.5249

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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