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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
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
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: 7.0729
## 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: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.1243 | 0.0206 | 8 | 2.2855 |
| 9.1803 | 0.0413 | 16 | 12.8133 |
| 9.137 | 0.0619 | 24 | 8.4567 |
| 8.3645 | 0.0825 | 32 | 8.2606 |
| 8.5251 | 0.1032 | 40 | 7.7564 |
| 9.4881 | 0.1238 | 48 | 9.3070 |
| 7.7111 | 0.1444 | 56 | 7.7363 |
| 7.6126 | 0.1651 | 64 | 7.5948 |
| 7.6789 | 0.1857 | 72 | 7.6147 |
| 7.7404 | 0.2063 | 80 | 7.6322 |
| 7.7173 | 0.2270 | 88 | 7.6740 |
| 7.7113 | 0.2476 | 96 | 7.6742 |
| 7.6961 | 0.2682 | 104 | 7.6422 |
| 7.6729 | 0.2888 | 112 | 7.6076 |
| 7.7225 | 0.3095 | 120 | 7.7171 |
| 7.8259 | 0.3301 | 128 | 7.7724 |
| 7.6611 | 0.3507 | 136 | 7.5974 |
| 7.5696 | 0.3714 | 144 | 7.6032 |
| 7.6786 | 0.3920 | 152 | 7.6163 |
| 7.4746 | 0.4126 | 160 | 7.4268 |
| 7.4383 | 0.4333 | 168 | 7.4069 |
| 7.4469 | 0.4539 | 176 | 7.5225 |
| 7.6465 | 0.4745 | 184 | 7.4849 |
| 7.4025 | 0.4952 | 192 | 7.3099 |
| 7.3473 | 0.5158 | 200 | 7.2623 |
| 7.2821 | 0.5364 | 208 | 7.2484 |
| 7.389 | 0.5571 | 216 | 7.7177 |
| 7.2912 | 0.5777 | 224 | 7.1141 |
| 7.1847 | 0.5983 | 232 | 7.1145 |
| 7.2121 | 0.6190 | 240 | 7.1465 |
| 7.1216 | 0.6396 | 248 | 7.1479 |
| 7.2503 | 0.6602 | 256 | 7.1105 |
| 7.1416 | 0.6809 | 264 | 7.1730 |
| 7.2288 | 0.7015 | 272 | 7.1491 |
| 7.3502 | 0.7221 | 280 | 7.1991 |
| 7.2648 | 0.7427 | 288 | 7.1406 |
| 7.1647 | 0.7634 | 296 | 7.1226 |
| 7.1678 | 0.7840 | 304 | 7.0843 |
| 7.1879 | 0.8046 | 312 | 7.1045 |
| 7.2384 | 0.8253 | 320 | 7.1137 |
| 7.2301 | 0.8459 | 328 | 7.0949 |
| 7.2897 | 0.8665 | 336 | 7.1273 |
| 7.1483 | 0.8872 | 344 | 7.1084 |
| 7.1119 | 0.9078 | 352 | 7.0984 |
| 7.2202 | 0.9284 | 360 | 7.0766 |
| 7.1149 | 0.9491 | 368 | 7.0738 |
| 7.1986 | 0.9697 | 376 | 7.0749 |
| 7.155 | 0.9903 | 384 | 7.0729 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |