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mistral-7b-autextification2024

PEFT
Safetensors
trl
sft
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metadata
license: apache-2.0
library_name: peft
tags:
  - trl
  - sft
  - generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
  - name: mistral-7b-autextification2024
    results: []

mistral-7b-autextification2024

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6422

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • lr_scheduler_warmup_ratio: 0.03
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
1.4251 0.0 10 1.7924
1.3175 0.01 20 1.7542
1.7841 0.01 30 1.7322
2.0421 0.01 40 1.7294
2.669 0.02 50 1.7471
1.314 0.02 60 1.7153
1.4678 0.02 70 1.6989
1.7679 0.03 80 1.6928
2.0057 0.03 90 1.7002
2.5086 0.03 100 1.7053
1.3326 0.04 110 1.6931
1.3984 0.04 120 1.6823
1.8045 0.04 130 1.6807
1.8764 0.05 140 1.6812
2.5524 0.05 150 1.6825
1.2854 0.05 160 1.6766
1.3712 0.06 170 1.6709
1.8211 0.06 180 1.6660
2.0365 0.06 190 1.6778
2.4664 0.07 200 1.6938
1.3405 0.07 210 1.6712
1.3856 0.07 220 1.6666
1.5553 0.08 230 1.6586
1.8616 0.08 240 1.6613
2.4064 0.09 250 1.6666
1.3446 0.09 260 1.6681
1.386 0.09 270 1.6645
1.6508 0.1 280 1.6582
1.8588 0.1 290 1.6600
2.3148 0.1 300 1.6524
1.2785 0.11 310 1.6549
1.2727 0.11 320 1.6517
1.5971 0.11 330 1.6486
1.7811 0.12 340 1.6540
2.3368 0.12 350 1.6596
1.2513 0.12 360 1.6578
1.4403 0.13 370 1.6429
1.8051 0.13 380 1.6462
1.8214 0.13 390 1.6469
2.4691 0.14 400 1.6654
1.2895 0.14 410 1.6543
1.3192 0.14 420 1.6435
1.7031 0.15 430 1.6438
1.8647 0.15 440 1.6402
2.398 0.15 450 1.6444
1.3195 0.16 460 1.6445
1.4008 0.16 470 1.6407
1.6925 0.16 480 1.6380
1.8432 0.17 490 1.6396
2.5103 0.17 500 1.6422

Framework versions

  • PEFT 0.10.0
  • Transformers 4.39.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2