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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: 1.1790
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.173 | 0.0261 | 4 | 1.2153 |
| 1.1501 | 0.0523 | 8 | 1.1905 |
| 1.19 | 0.0784 | 12 | 1.1831 |
| 1.0875 | 0.1046 | 16 | 1.1805 |
| 1.1648 | 0.1307 | 20 | 1.1844 |
| 1.077 | 0.1569 | 24 | 1.1861 |
| 1.2251 | 0.1830 | 28 | 1.1925 |
| 1.1615 | 0.2092 | 32 | 1.1922 |
| 1.1153 | 0.2353 | 36 | 1.1763 |
| 1.2024 | 0.2614 | 40 | 1.1803 |
| 1.2181 | 0.2876 | 44 | 1.1724 |
| 1.1503 | 0.3137 | 48 | 1.2055 |
| 1.1639 | 0.3399 | 52 | 1.1896 |
| 1.1405 | 0.3660 | 56 | 1.1827 |
| 1.177 | 0.3922 | 60 | 1.2037 |
| 1.1958 | 0.4183 | 64 | 1.1796 |
| 1.1044 | 0.4444 | 68 | 1.1970 |
| 1.1115 | 0.4706 | 72 | 1.1735 |
| 1.1152 | 0.4967 | 76 | 1.2061 |
| 1.2009 | 0.5229 | 80 | 1.1671 |
| 1.1154 | 0.5490 | 84 | 1.1960 |
| 1.1739 | 0.5752 | 88 | 1.1892 |
| 1.2224 | 0.6013 | 92 | 1.1764 |
| 1.2229 | 0.6275 | 96 | 1.1926 |
| 1.1573 | 0.6536 | 100 | 1.1849 |
| 1.1629 | 0.6797 | 104 | 1.1787 |
| 1.1855 | 0.7059 | 108 | 1.1955 |
| 1.0586 | 0.7320 | 112 | 1.1814 |
| 1.1258 | 0.7582 | 116 | 1.1631 |
| 1.1273 | 0.7843 | 120 | 1.1787 |
| 1.1869 | 0.8105 | 124 | 1.1873 |
| 1.1765 | 0.8366 | 128 | 1.1852 |
| 1.1954 | 0.8627 | 132 | 1.1809 |
| 1.1277 | 0.8889 | 136 | 1.1763 |
| 1.2109 | 0.9150 | 140 | 1.1747 |
| 1.0842 | 0.9412 | 144 | 1.1771 |
| 1.0941 | 0.9673 | 148 | 1.1787 |
| 1.2413 | 0.9935 | 152 | 1.1790 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |