lora_final / README.md
imdatta0's picture
End of training
813fbff verified
|
raw
history blame
3.97 kB
metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
  - unsloth
  - generated_from_trainer
model-index:
  - name: lora_final
    results: []

lora_final

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2365

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.02
  • num_epochs: 0.3

Training results

Training Loss Epoch Step Validation Loss
1.3759 0.0065 1 1.3988
1.4834 0.0130 2 1.3942
1.255 0.0194 3 1.3840
1.2544 0.0259 4 1.3690
1.4768 0.0324 5 1.3500
1.293 0.0389 6 1.3319
1.2655 0.0453 7 1.3147
1.3413 0.0518 8 1.3033
1.2213 0.0583 9 1.2943
1.2445 0.0648 10 1.2885
1.2504 0.0713 11 1.2847
1.2629 0.0777 12 1.2826
1.3952 0.0842 13 1.2806
1.2751 0.0907 14 1.2773
1.283 0.0972 15 1.2744
1.2798 0.1036 16 1.2706
1.2756 0.1101 17 1.2669
1.1372 0.1166 18 1.2634
1.2445 0.1231 19 1.2600
1.3368 0.1296 20 1.2566
1.3386 0.1360 21 1.2534
1.1837 0.1425 22 1.2503
1.2373 0.1490 23 1.2482
1.1467 0.1555 24 1.2463
1.1782 0.1619 25 1.2447
1.1786 0.1684 26 1.2437
1.2298 0.1749 27 1.2430
1.2577 0.1814 28 1.2424
1.2813 0.1879 29 1.2415
1.2026 0.1943 30 1.2409
1.283 0.2008 31 1.2403
1.1598 0.2073 32 1.2396
1.2361 0.2138 33 1.2389
1.2846 0.2202 34 1.2386
1.3396 0.2267 35 1.2380
1.1525 0.2332 36 1.2377
1.1395 0.2397 37 1.2373
1.1794 0.2462 38 1.2370
1.332 0.2526 39 1.2369
1.2646 0.2591 40 1.2368
1.3159 0.2656 41 1.2367
1.1981 0.2721 42 1.2365
1.3205 0.2785 43 1.2365
1.1876 0.2850 44 1.2366
1.3331 0.2915 45 1.2365
1.1288 0.2980 46 1.2366
1.1745 0.3045 47 1.2366
1.1716 0.3109 48 1.2366
1.2834 0.3174 49 1.2365

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1