File size: 3,103 Bytes
48d66e6 |
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 |
---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
model-index:
- name: PHI30512HMAB3H
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. -->
# PHI30512HMAB3H
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: 0.0270
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.997 | 0.09 | 10 | 1.9314 |
| 0.8757 | 0.18 | 20 | 0.2981 |
| 0.313 | 0.27 | 30 | 0.2856 |
| 0.2921 | 0.36 | 40 | 0.2521 |
| 0.2598 | 0.45 | 50 | 0.2293 |
| 0.237 | 0.54 | 60 | 0.2495 |
| 0.2258 | 0.63 | 70 | 0.2233 |
| 0.2146 | 0.73 | 80 | 0.1941 |
| 0.2096 | 0.82 | 90 | 0.2012 |
| 0.1865 | 0.91 | 100 | 0.1695 |
| 0.1751 | 1.0 | 110 | 0.1659 |
| 0.1633 | 1.09 | 120 | 0.1674 |
| 0.17 | 1.18 | 130 | 0.1656 |
| 0.1734 | 1.27 | 140 | 0.1610 |
| 0.1633 | 1.36 | 150 | 0.1478 |
| 0.1548 | 1.45 | 160 | 0.1397 |
| 0.1564 | 1.54 | 170 | 0.1275 |
| 0.1377 | 1.63 | 180 | 0.1395 |
| 0.1093 | 1.72 | 190 | 0.0882 |
| 0.1058 | 1.81 | 200 | 0.0842 |
| 0.0908 | 1.9 | 210 | 0.0833 |
| 0.0662 | 1.99 | 220 | 0.0539 |
| 0.1051 | 2.08 | 230 | 0.1356 |
| 0.1601 | 2.18 | 240 | 0.1337 |
| 0.1836 | 2.27 | 250 | 0.0889 |
| 0.067 | 2.36 | 260 | 0.0608 |
| 0.0626 | 2.45 | 270 | 0.0509 |
| 0.0477 | 2.54 | 280 | 0.0431 |
| 0.0411 | 2.63 | 290 | 0.0390 |
| 0.0349 | 2.72 | 300 | 0.0331 |
| 0.0338 | 2.81 | 310 | 0.0298 |
| 0.0288 | 2.9 | 320 | 0.0284 |
| 0.0302 | 2.99 | 330 | 0.0270 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
|