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---
base_model: mistralai/Mistral-7B-v0.3
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_pct_default_r32
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_default_r32
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0448
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9915 | 0.0206 | 8 | 2.0385 |
| 2.054 | 0.0413 | 16 | 2.0376 |
| 2.0356 | 0.0619 | 24 | 2.0604 |
| 2.0385 | 0.0825 | 32 | 2.0639 |
| 2.1223 | 0.1032 | 40 | 2.0833 |
| 2.0677 | 0.1238 | 48 | 2.0910 |
| 2.0729 | 0.1444 | 56 | 2.0872 |
| 2.1197 | 0.1651 | 64 | 2.0973 |
| 2.1053 | 0.1857 | 72 | 2.0919 |
| 2.0848 | 0.2063 | 80 | 2.1035 |
| 2.1015 | 0.2270 | 88 | 2.1114 |
| 2.0872 | 0.2476 | 96 | 2.1133 |
| 2.0948 | 0.2682 | 104 | 2.1221 |
| 2.097 | 0.2889 | 112 | 2.1219 |
| 2.147 | 0.3095 | 120 | 2.1240 |
| 2.1315 | 0.3301 | 128 | 2.1189 |
| 2.1563 | 0.3508 | 136 | 2.1368 |
| 2.1836 | 0.3714 | 144 | 2.1271 |
| 2.1245 | 0.3920 | 152 | 2.1198 |
| 2.0947 | 0.4127 | 160 | 2.1240 |
| 2.1472 | 0.4333 | 168 | 2.1354 |
| 2.1348 | 0.4539 | 176 | 2.1261 |
| 2.1099 | 0.4746 | 184 | 2.1275 |
| 2.1006 | 0.4952 | 192 | 2.1196 |
| 2.1339 | 0.5158 | 200 | 2.1170 |
| 2.0841 | 0.5364 | 208 | 2.1105 |
| 2.1344 | 0.5571 | 216 | 2.1079 |
| 2.0732 | 0.5777 | 224 | 2.1043 |
| 2.0417 | 0.5983 | 232 | 2.1035 |
| 2.1003 | 0.6190 | 240 | 2.0967 |
| 2.0501 | 0.6396 | 248 | 2.1007 |
| 2.078 | 0.6602 | 256 | 2.0862 |
| 2.0507 | 0.6809 | 264 | 2.0840 |
| 2.0235 | 0.7015 | 272 | 2.0762 |
| 2.0743 | 0.7221 | 280 | 2.0723 |
| 2.1028 | 0.7428 | 288 | 2.0721 |
| 2.0987 | 0.7634 | 296 | 2.0662 |
| 2.0985 | 0.7840 | 304 | 2.0663 |
| 2.0548 | 0.8047 | 312 | 2.0602 |
| 2.0365 | 0.8253 | 320 | 2.0563 |
| 2.0102 | 0.8459 | 328 | 2.0564 |
| 2.0497 | 0.8666 | 336 | 2.0522 |
| 2.0721 | 0.8872 | 344 | 2.0471 |
| 2.0812 | 0.9078 | 352 | 2.0468 |
| 2.0475 | 0.9285 | 360 | 2.0462 |
| 2.0687 | 0.9491 | 368 | 2.0452 |
| 2.065 | 0.9697 | 376 | 2.0450 |
| 1.991 | 0.9904 | 384 | 2.0448 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1 |