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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_reverse_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_reverse_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: 2.0458
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.991 | 0.0206 | 8 | 2.0312 |
| 2.0461 | 0.0413 | 16 | 2.0335 |
| 2.0456 | 0.0619 | 24 | 2.0601 |
| 2.0584 | 0.0825 | 32 | 2.0879 |
| 2.1123 | 0.1032 | 40 | 2.0809 |
| 2.0666 | 0.1238 | 48 | 2.0890 |
| 2.0733 | 0.1444 | 56 | 2.0954 |
| 2.1236 | 0.1651 | 64 | 2.0971 |
| 2.1103 | 0.1857 | 72 | 2.1008 |
| 2.0876 | 0.2063 | 80 | 2.1042 |
| 2.1107 | 0.2270 | 88 | 2.1155 |
| 2.0889 | 0.2476 | 96 | 2.1083 |
| 2.097 | 0.2682 | 104 | 2.1186 |
| 2.0962 | 0.2889 | 112 | 2.1202 |
| 2.1415 | 0.3095 | 120 | 2.1305 |
| 2.1294 | 0.3301 | 128 | 2.1169 |
| 2.1476 | 0.3508 | 136 | 2.1300 |
| 2.1725 | 0.3714 | 144 | 2.1245 |
| 2.1159 | 0.3920 | 152 | 2.1172 |
| 2.0921 | 0.4127 | 160 | 2.1221 |
| 2.141 | 0.4333 | 168 | 2.1334 |
| 2.1312 | 0.4539 | 176 | 2.1259 |
| 2.106 | 0.4746 | 184 | 2.1269 |
| 2.1015 | 0.4952 | 192 | 2.1197 |
| 2.1368 | 0.5158 | 200 | 2.1164 |
| 2.0751 | 0.5364 | 208 | 2.1104 |
| 2.135 | 0.5571 | 216 | 2.1105 |
| 2.0718 | 0.5777 | 224 | 2.1003 |
| 2.0393 | 0.5983 | 232 | 2.1025 |
| 2.1034 | 0.6190 | 240 | 2.0946 |
| 2.045 | 0.6396 | 248 | 2.0939 |
| 2.077 | 0.6602 | 256 | 2.0814 |
| 2.0514 | 0.6809 | 264 | 2.0800 |
| 2.0222 | 0.7015 | 272 | 2.0774 |
| 2.075 | 0.7221 | 280 | 2.0749 |
| 2.1013 | 0.7428 | 288 | 2.0705 |
| 2.0929 | 0.7634 | 296 | 2.0643 |
| 2.0996 | 0.7840 | 304 | 2.0692 |
| 2.0507 | 0.8047 | 312 | 2.0588 |
| 2.0353 | 0.8253 | 320 | 2.0574 |
| 2.0128 | 0.8459 | 328 | 2.0570 |
| 2.0508 | 0.8666 | 336 | 2.0503 |
| 2.067 | 0.8872 | 344 | 2.0472 |
| 2.0821 | 0.9078 | 352 | 2.0476 |
| 2.0461 | 0.9285 | 360 | 2.0471 |
| 2.0666 | 0.9491 | 368 | 2.0461 |
| 2.0639 | 0.9697 | 376 | 2.0458 |
| 1.9859 | 0.9904 | 384 | 2.0458 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1 |