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---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_magiccoder_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_magiccoder_ortho
This model is a fine-tuned version of [unsloth/mistral-7b-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.8291
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.2179 | 0.0262 | 4 | 1.6151 |
| 4.1153 | 0.0523 | 8 | 11.4846 |
| 9.4045 | 0.0785 | 12 | 10.9796 |
| 8.1663 | 0.1047 | 16 | 8.2167 |
| 9.0474 | 0.1308 | 20 | 10.0032 |
| 8.4796 | 0.1570 | 24 | 8.3873 |
| 7.9286 | 0.1832 | 28 | 8.0296 |
| 7.8704 | 0.2093 | 32 | 7.9253 |
| 7.7139 | 0.2355 | 36 | 7.8579 |
| 7.9416 | 0.2617 | 40 | 7.7372 |
| 7.9342 | 0.2878 | 44 | 7.8272 |
| 7.7907 | 0.3140 | 48 | 7.8569 |
| 7.9106 | 0.3401 | 52 | 7.8776 |
| 7.8242 | 0.3663 | 56 | 7.8943 |
| 7.8321 | 0.3925 | 60 | 7.8261 |
| 7.861 | 0.4186 | 64 | 7.8201 |
| 7.9374 | 0.4448 | 68 | 7.8658 |
| 7.8396 | 0.4710 | 72 | 7.8735 |
| 7.8607 | 0.4971 | 76 | 7.8436 |
| 7.9294 | 0.5233 | 80 | 7.8951 |
| 7.9017 | 0.5495 | 84 | 7.8877 |
| 7.8512 | 0.5756 | 88 | 7.8694 |
| 7.9036 | 0.6018 | 92 | 7.8331 |
| 7.8496 | 0.6280 | 96 | 7.8269 |
| 7.8837 | 0.6541 | 100 | 7.8142 |
| 7.8718 | 0.6803 | 104 | 7.9025 |
| 7.934 | 0.7065 | 108 | 7.8767 |
| 7.8706 | 0.7326 | 112 | 7.8579 |
| 7.8889 | 0.7588 | 116 | 7.8467 |
| 7.8279 | 0.7850 | 120 | 7.7952 |
| 7.9176 | 0.8111 | 124 | 7.8180 |
| 7.8894 | 0.8373 | 128 | 7.8068 |
| 7.8625 | 0.8635 | 132 | 7.8081 |
| 7.8447 | 0.8896 | 136 | 7.8196 |
| 7.7559 | 0.9158 | 140 | 7.8307 |
| 7.8508 | 0.9419 | 144 | 7.8304 |
| 7.8058 | 0.9681 | 148 | 7.8295 |
| 7.8377 | 0.9943 | 152 | 7.8291 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |