File size: 3,917 Bytes
8b1b653 |
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 99 100 101 102 103 104 105 106 107 108 109 110 |
---
base_model: unsloth/mistral-7b-v0.3
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_pct_reverse_r16
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. -->
# Mistral-7B-v0.3_pct_reverse_r16
This model is a fine-tuned version of [unsloth/mistral-7b-v0.3](https://huggingface.co/unsloth/mistral-7b-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0162
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.9648 | 0.0206 | 8 | 2.0392 |
| 2.0599 | 0.0413 | 16 | 2.0531 |
| 2.1274 | 0.0619 | 24 | 2.0571 |
| 2.0718 | 0.0825 | 32 | 2.0473 |
| 2.0646 | 0.1032 | 40 | 2.0420 |
| 2.0883 | 0.1238 | 48 | 2.0460 |
| 2.0611 | 0.1445 | 56 | 2.0497 |
| 2.0841 | 0.1651 | 64 | 2.0536 |
| 2.0695 | 0.1857 | 72 | 2.0688 |
| 2.0696 | 0.2064 | 80 | 2.0792 |
| 2.1315 | 0.2270 | 88 | 2.0900 |
| 2.1466 | 0.2476 | 96 | 2.0827 |
| 2.1575 | 0.2683 | 104 | 2.0826 |
| 2.0925 | 0.2889 | 112 | 2.0864 |
| 2.1647 | 0.3096 | 120 | 2.0815 |
| 2.1018 | 0.3302 | 128 | 2.0882 |
| 2.1062 | 0.3508 | 136 | 2.0904 |
| 2.1596 | 0.3715 | 144 | 2.0847 |
| 2.1473 | 0.3921 | 152 | 2.0933 |
| 2.1388 | 0.4127 | 160 | 2.0888 |
| 2.093 | 0.4334 | 168 | 2.0887 |
| 2.1704 | 0.4540 | 176 | 2.0933 |
| 2.0697 | 0.4746 | 184 | 2.0779 |
| 2.1725 | 0.4953 | 192 | 2.0714 |
| 2.1339 | 0.5159 | 200 | 2.0695 |
| 2.106 | 0.5366 | 208 | 2.0640 |
| 2.0857 | 0.5572 | 216 | 2.0792 |
| 2.0751 | 0.5778 | 224 | 2.0658 |
| 2.0987 | 0.5985 | 232 | 2.0659 |
| 2.0817 | 0.6191 | 240 | 2.0628 |
| 2.1341 | 0.6397 | 248 | 2.0564 |
| 2.0567 | 0.6604 | 256 | 2.0517 |
| 2.1246 | 0.6810 | 264 | 2.0457 |
| 2.0623 | 0.7017 | 272 | 2.0423 |
| 2.1106 | 0.7223 | 280 | 2.0369 |
| 2.1094 | 0.7429 | 288 | 2.0375 |
| 2.0678 | 0.7636 | 296 | 2.0330 |
| 2.0521 | 0.7842 | 304 | 2.0326 |
| 2.0594 | 0.8048 | 312 | 2.0241 |
| 2.051 | 0.8255 | 320 | 2.0208 |
| 2.0392 | 0.8461 | 328 | 2.0201 |
| 2.0143 | 0.8667 | 336 | 2.0207 |
| 2.0678 | 0.8874 | 344 | 2.0222 |
| 2.0473 | 0.9080 | 352 | 2.0187 |
| 2.0324 | 0.9287 | 360 | 2.0165 |
| 2.0404 | 0.9493 | 368 | 2.0160 |
| 2.0426 | 0.9699 | 376 | 2.0163 |
| 2.0635 | 0.9906 | 384 | 2.0162 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |