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abhishekyo/finetune8
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metadata
license: llama2
library_name: peft
tags:
  - trl
  - sft
  - generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
  - name: codellama2-finetuned-codex
    results: []

codellama2-finetuned-codex

This model is a fine-tuned version of codellama/CodeLlama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2549

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: 4e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • 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: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.876 0.43 20 1.7743
1.6213 0.85 40 1.4426
1.0392 1.28 60 0.9086
0.6962 1.7 80 0.6664
0.529 2.13 100 0.5439
0.4614 2.55 120 0.4650
0.4264 2.98 140 0.4218
0.376 3.4 160 0.3951
0.3665 3.83 180 0.3722
0.3398 4.26 200 0.3559
0.3198 4.68 220 0.3389
0.3263 5.11 240 0.3317
0.2952 5.53 260 0.3223
0.2871 5.96 280 0.3136
0.2861 6.38 300 0.3084
0.2899 6.81 320 0.3021
0.2769 7.23 340 0.2982
0.2541 7.66 360 0.2951
0.2421 8.09 380 0.2914
0.2275 8.51 400 0.2887
0.26 8.94 420 0.2799
0.2275 9.36 440 0.2797
0.2291 9.79 460 0.2722
0.2222 10.21 480 0.2744
0.2391 10.64 500 0.2721
0.208 11.06 520 0.2671
0.2012 11.49 540 0.2691
0.2092 11.91 560 0.2619
0.1761 12.34 580 0.2636
0.2248 12.77 600 0.2596
0.1803 13.19 620 0.2611
0.2022 13.62 640 0.2597
0.2006 14.04 660 0.2578
0.1864 14.47 680 0.2561
0.1933 14.89 700 0.2560
0.1892 15.32 720 0.2570
0.192 15.74 740 0.2562
0.1883 16.17 760 0.2553
0.1781 16.6 780 0.2549
0.1705 17.02 800 0.2560
0.181 17.45 820 0.2566
0.1552 17.87 840 0.2551
0.173 18.3 860 0.2560
0.1934 18.72 880 0.2557
0.1754 19.15 900 0.2555
0.1796 19.57 920 0.2555
0.1745 20.0 940 0.2555

Framework versions

  • PEFT 0.10.0
  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2