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Llama-3.2-1B-Instruct_v2

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Llama-3.2-1B-Instruct_v2 / README.md
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metadata
base_model: meta-llama/Llama-3.2-1B-Instruct
library_name: peft
license: llama3.2
tags:
  - generated_from_trainer
model-index:
  - name: Llama-3.2-1B-Instruct_v2
    results: []

Llama-3.2-1B-Instruct_v2

This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2356

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: 0.0005
  • 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_steps: 30
  • training_steps: 3000

Training results

Training Loss Epoch Step Validation Loss
0.4565 0.0333 100 0.4058
0.3313 0.0667 200 0.3428
0.3139 0.1 300 0.3192
0.2903 0.1333 400 0.3034
0.2639 0.1667 500 0.2944
0.2688 0.2 600 0.2869
0.3097 0.2333 700 0.2791
0.2462 0.2667 800 0.2735
0.3257 0.3 900 0.2684
0.2738 0.3333 1000 0.2638
0.2572 0.3667 1100 0.2598
0.234 0.4 1200 0.2566
0.2233 0.4333 1300 0.2537
0.2996 0.4667 1400 0.2515
0.2178 0.5 1500 0.2490
0.2251 0.5333 1600 0.2470
0.262 0.5667 1700 0.2450
0.2683 0.6 1800 0.2430
0.1966 0.6333 1900 0.2416
0.2451 0.6667 2000 0.2403
0.2247 0.7 2100 0.2393
0.1865 0.7333 2200 0.2384
0.2837 0.7667 2300 0.2378
0.2312 0.8 2400 0.2371
0.239 0.8333 2500 0.2365
0.2064 0.8667 2600 0.2362
0.208 0.9 2700 0.2358
0.2588 0.9333 2800 0.2356
0.2029 0.9667 2900 0.2356
0.2404 1.0 3000 0.2356

Framework versions

  • PEFT 0.13.2
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1