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---
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_ortho_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_ortho_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: 2.0091
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9566 | 0.0206 | 8 | 2.0118 |
| 2.0191 | 0.0413 | 16 | 1.9983 |
| 2.0779 | 0.0619 | 24 | 2.0212 |
| 2.0339 | 0.0825 | 32 | 2.0205 |
| 2.0429 | 0.1032 | 40 | 2.0132 |
| 2.0601 | 0.1238 | 48 | 2.0219 |
| 2.041 | 0.1445 | 56 | 2.0171 |
| 2.0602 | 0.1651 | 64 | 2.0230 |
| 2.0341 | 0.1857 | 72 | 2.0311 |
| 2.0378 | 0.2064 | 80 | 2.0319 |
| 2.0961 | 0.2270 | 88 | 2.0402 |
| 2.106 | 0.2476 | 96 | 2.0208 |
| 2.1219 | 0.2683 | 104 | 2.0328 |
| 2.0569 | 0.2889 | 112 | 2.0528 |
| 2.1062 | 0.3096 | 120 | 2.0355 |
| 2.0522 | 0.3302 | 128 | 2.0365 |
| 2.0631 | 0.3508 | 136 | 2.0300 |
| 2.1052 | 0.3715 | 144 | 2.0409 |
| 2.0875 | 0.3921 | 152 | 2.0454 |
| 2.0854 | 0.4127 | 160 | 2.0273 |
| 2.0533 | 0.4334 | 168 | 2.0529 |
| 2.1096 | 0.4540 | 176 | 2.0373 |
| 2.0288 | 0.4746 | 184 | 2.0289 |
| 2.1344 | 0.4953 | 192 | 2.0375 |
| 2.0952 | 0.5159 | 200 | 2.0445 |
| 2.0613 | 0.5366 | 208 | 2.0374 |
| 2.0441 | 0.5572 | 216 | 2.0225 |
| 2.0493 | 0.5778 | 224 | 2.0380 |
| 2.0568 | 0.5985 | 232 | 2.0219 |
| 2.0477 | 0.6191 | 240 | 2.0261 |
| 2.1065 | 0.6397 | 248 | 2.0310 |
| 2.0245 | 0.6604 | 256 | 2.0208 |
| 2.1013 | 0.6810 | 264 | 2.0270 |
| 2.0356 | 0.7017 | 272 | 2.0205 |
| 2.0815 | 0.7223 | 280 | 2.0117 |
| 2.0898 | 0.7429 | 288 | 2.0175 |
| 2.0529 | 0.7636 | 296 | 2.0171 |
| 2.0281 | 0.7842 | 304 | 2.0134 |
| 2.0473 | 0.8048 | 312 | 2.0150 |
| 2.0315 | 0.8255 | 320 | 2.0088 |
| 2.0215 | 0.8461 | 328 | 2.0071 |
| 2.0003 | 0.8667 | 336 | 2.0093 |
| 2.0561 | 0.8874 | 344 | 2.0136 |
| 2.0407 | 0.9080 | 352 | 2.0132 |
| 2.0257 | 0.9287 | 360 | 2.0105 |
| 2.0294 | 0.9493 | 368 | 2.0090 |
| 2.0321 | 0.9699 | 376 | 2.0089 |
| 2.0516 | 0.9906 | 384 | 2.0091 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |