File size: 2,985 Bytes
220f4ef |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama-3.2-1B-Instruct_v2
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/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 |