File size: 3,919 Bytes
708dc5e |
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 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 |
---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: hf_phi3_lora
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/hmosousa/huggingface/runs/jy8rtirf)
# hf_phi3_lora
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3171
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.4828 | 0.1489 | 500 | 1.4306 |
| 1.4047 | 0.2978 | 1000 | 1.3980 |
| 1.3611 | 0.4468 | 1500 | 1.3835 |
| 1.3653 | 0.5957 | 2000 | 1.3709 |
| 1.3171 | 0.7446 | 2500 | 1.3665 |
| 1.3089 | 0.8935 | 3000 | 1.3626 |
| 1.312 | 1.0425 | 3500 | 1.3608 |
| 1.2771 | 1.1914 | 4000 | 1.3556 |
| 1.3031 | 1.3403 | 4500 | 1.3570 |
| 1.284 | 1.4892 | 5000 | 1.3508 |
| 1.2697 | 1.6382 | 5500 | 1.3477 |
| 1.2594 | 1.7871 | 6000 | 1.3453 |
| 1.254 | 1.9360 | 6500 | 1.3413 |
| 1.2652 | 2.0849 | 7000 | 1.3426 |
| 1.2529 | 2.2338 | 7500 | 1.3435 |
| 1.2544 | 2.3828 | 8000 | 1.3382 |
| 1.2511 | 2.5317 | 8500 | 1.3396 |
| 1.2548 | 2.6806 | 9000 | 1.3361 |
| 1.2483 | 2.8295 | 9500 | 1.3351 |
| 1.2442 | 2.9785 | 10000 | 1.3382 |
| 1.2426 | 3.1274 | 10500 | 1.3344 |
| 1.2265 | 3.2763 | 11000 | 1.3361 |
| 1.2255 | 3.4252 | 11500 | 1.3356 |
| 1.2269 | 3.5742 | 12000 | 1.3314 |
| 1.2396 | 3.7231 | 12500 | 1.3298 |
| 1.2303 | 3.8720 | 13000 | 1.3260 |
| 1.2254 | 4.0209 | 13500 | 1.3277 |
| 1.2277 | 4.1698 | 14000 | 1.3272 |
| 1.2295 | 4.3188 | 14500 | 1.3240 |
| 1.2375 | 4.4677 | 15000 | 1.3288 |
| 1.2038 | 4.6166 | 15500 | 1.3224 |
| 1.2322 | 4.7655 | 16000 | 1.3214 |
| 1.2015 | 4.9145 | 16500 | 1.3246 |
| 1.208 | 5.0634 | 17000 | 1.3216 |
| 1.2248 | 5.2123 | 17500 | 1.3193 |
| 1.2155 | 5.3612 | 18000 | 1.3249 |
| 1.2194 | 5.5102 | 18500 | 1.3183 |
| 1.2185 | 5.6591 | 19000 | 1.3196 |
| 1.2119 | 5.8080 | 19500 | 1.3142 |
| 1.2171 | 5.9569 | 20000 | 1.3240 |
| 1.21 | 6.1058 | 20500 | 1.3235 |
| 1.19 | 6.2548 | 21000 | 1.3171 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1 |