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---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.3
model-index:
- name: mistral_7b_v_Magiccoder_evol_10k_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_v_Magiccoder_evol_10k_ortho
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: 1.1371
## 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: 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_steps: 0.02
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1548 | 0.0262 | 4 | 1.1975 |
| 1.1117 | 0.0523 | 8 | 1.1750 |
| 1.1638 | 0.0785 | 12 | 1.1670 |
| 1.0902 | 0.1047 | 16 | 1.1675 |
| 1.1292 | 0.1308 | 20 | 1.1671 |
| 1.0469 | 0.1570 | 24 | 1.1621 |
| 1.2005 | 0.1832 | 28 | 1.1638 |
| 1.1491 | 0.2093 | 32 | 1.1638 |
| 1.0749 | 0.2355 | 36 | 1.1475 |
| 1.1758 | 0.2617 | 40 | 1.1525 |
| 1.1511 | 0.2878 | 44 | 1.1410 |
| 1.1229 | 0.3140 | 48 | 1.1532 |
| 1.1349 | 0.3401 | 52 | 1.1592 |
| 1.1116 | 0.3663 | 56 | 1.1465 |
| 1.1127 | 0.3925 | 60 | 1.1517 |
| 1.1709 | 0.4186 | 64 | 1.1460 |
| 1.0574 | 0.4448 | 68 | 1.1504 |
| 1.0794 | 0.4710 | 72 | 1.1414 |
| 1.0711 | 0.4971 | 76 | 1.1485 |
| 1.1984 | 0.5233 | 80 | 1.1544 |
| 1.0625 | 0.5495 | 84 | 1.1346 |
| 1.151 | 0.5756 | 88 | 1.1728 |
| 1.1977 | 0.6018 | 92 | 1.1364 |
| 1.1757 | 0.6280 | 96 | 1.1418 |
| 1.1191 | 0.6541 | 100 | 1.1487 |
| 1.1415 | 0.6803 | 104 | 1.1431 |
| 1.1272 | 0.7065 | 108 | 1.1399 |
| 1.0134 | 0.7326 | 112 | 1.1431 |
| 1.09 | 0.7588 | 116 | 1.1261 |
| 1.0848 | 0.7850 | 120 | 1.1346 |
| 1.1346 | 0.8111 | 124 | 1.1401 |
| 1.1336 | 0.8373 | 128 | 1.1371 |
| 1.1458 | 0.8635 | 132 | 1.1338 |
| 1.0835 | 0.8896 | 136 | 1.1334 |
| 1.1795 | 0.9158 | 140 | 1.1345 |
| 1.0422 | 0.9419 | 144 | 1.1359 |
| 1.0608 | 0.9681 | 148 | 1.1367 |
| 1.2045 | 0.9943 | 152 | 1.1371 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |