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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_default_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_default_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: 2.0180
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9646 | 0.0206 | 8 | 2.0348 |
| 2.0531 | 0.0413 | 16 | 2.0345 |
| 2.1168 | 0.0619 | 24 | 2.0464 |
| 2.0712 | 0.0825 | 32 | 2.0462 |
| 2.0779 | 0.1032 | 40 | 2.0510 |
| 2.0905 | 0.1238 | 48 | 2.0476 |
| 2.0624 | 0.1445 | 56 | 2.0475 |
| 2.0793 | 0.1651 | 64 | 2.0428 |
| 2.0559 | 0.1857 | 72 | 2.0521 |
| 2.0597 | 0.2064 | 80 | 2.0680 |
| 2.1235 | 0.2270 | 88 | 2.0849 |
| 2.14 | 0.2476 | 96 | 2.0772 |
| 2.1586 | 0.2683 | 104 | 2.0880 |
| 2.0974 | 0.2889 | 112 | 2.0837 |
| 2.1577 | 0.3096 | 120 | 2.0838 |
| 2.0998 | 0.3302 | 128 | 2.0899 |
| 2.1069 | 0.3508 | 136 | 2.0882 |
| 2.1621 | 0.3715 | 144 | 2.0846 |
| 2.1441 | 0.3921 | 152 | 2.0949 |
| 2.1355 | 0.4127 | 160 | 2.0859 |
| 2.084 | 0.4334 | 168 | 2.0871 |
| 2.1649 | 0.4540 | 176 | 2.0845 |
| 2.0651 | 0.4746 | 184 | 2.0719 |
| 2.1708 | 0.4953 | 192 | 2.0722 |
| 2.1311 | 0.5159 | 200 | 2.0677 |
| 2.1038 | 0.5366 | 208 | 2.0627 |
| 2.0804 | 0.5572 | 216 | 2.0757 |
| 2.0695 | 0.5778 | 224 | 2.0649 |
| 2.0961 | 0.5985 | 232 | 2.0643 |
| 2.0808 | 0.6191 | 240 | 2.0567 |
| 2.1337 | 0.6397 | 248 | 2.0557 |
| 2.0565 | 0.6604 | 256 | 2.0555 |
| 2.1184 | 0.6810 | 264 | 2.0497 |
| 2.0604 | 0.7017 | 272 | 2.0412 |
| 2.1099 | 0.7223 | 280 | 2.0384 |
| 2.1048 | 0.7429 | 288 | 2.0415 |
| 2.0692 | 0.7636 | 296 | 2.0340 |
| 2.0489 | 0.7842 | 304 | 2.0331 |
| 2.057 | 0.8048 | 312 | 2.0275 |
| 2.0485 | 0.8255 | 320 | 2.0224 |
| 2.0364 | 0.8461 | 328 | 2.0202 |
| 2.014 | 0.8667 | 336 | 2.0240 |
| 2.0656 | 0.8874 | 344 | 2.0236 |
| 2.0473 | 0.9080 | 352 | 2.0197 |
| 2.0279 | 0.9287 | 360 | 2.0180 |
| 2.0415 | 0.9493 | 368 | 2.0178 |
| 2.0419 | 0.9699 | 376 | 2.0178 |
| 2.0597 | 0.9906 | 384 | 2.0180 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |