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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: mistralai_mistral_7b_v0.3_imdatta0_Magiccoder_evol_10k_reverse
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. -->
# mistralai_mistral_7b_v0.3_imdatta0_Magiccoder_evol_10k_reverse
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: 1.1504
## 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_ratio: 0.02
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1815 | 0.0262 | 4 | 1.2461 |
| 1.1779 | 0.0523 | 8 | 1.2277 |
| 1.2145 | 0.0785 | 12 | 1.2208 |
| 1.1589 | 0.1047 | 16 | 1.2399 |
| 1.2113 | 0.1308 | 20 | 1.2424 |
| 1.1171 | 0.1570 | 24 | 1.2347 |
| 1.2649 | 0.1832 | 28 | 1.2280 |
| 1.2005 | 0.2093 | 32 | 1.2154 |
| 1.1418 | 0.2355 | 36 | 1.2183 |
| 1.1896 | 0.2617 | 40 | 1.2063 |
| 1.2135 | 0.2878 | 44 | 1.2015 |
| 1.1641 | 0.3140 | 48 | 1.2015 |
| 1.1855 | 0.3401 | 52 | 1.2107 |
| 1.1493 | 0.3663 | 56 | 1.1929 |
| 1.168 | 0.3925 | 60 | 1.1938 |
| 1.2119 | 0.4186 | 64 | 1.2076 |
| 1.1207 | 0.4448 | 68 | 1.2077 |
| 1.1249 | 0.4710 | 72 | 1.1969 |
| 1.1242 | 0.4971 | 76 | 1.1923 |
| 1.2203 | 0.5233 | 80 | 1.1874 |
| 1.1168 | 0.5495 | 84 | 1.1766 |
| 1.1781 | 0.5756 | 88 | 1.1852 |
| 1.2153 | 0.6018 | 92 | 1.1785 |
| 1.213 | 0.6280 | 96 | 1.1682 |
| 1.1424 | 0.6541 | 100 | 1.1693 |
| 1.1577 | 0.6803 | 104 | 1.1702 |
| 1.1586 | 0.7065 | 108 | 1.1736 |
| 1.0325 | 0.7326 | 112 | 1.1546 |
| 1.1151 | 0.7588 | 116 | 1.1556 |
| 1.1153 | 0.7850 | 120 | 1.1539 |
| 1.1471 | 0.8111 | 124 | 1.1512 |
| 1.1408 | 0.8373 | 128 | 1.1488 |
| 1.1676 | 0.8635 | 132 | 1.1485 |
| 1.1049 | 0.8896 | 136 | 1.1489 |
| 1.1905 | 0.9158 | 140 | 1.1494 |
| 1.0539 | 0.9419 | 144 | 1.1500 |
| 1.0729 | 0.9681 | 148 | 1.1503 |
| 1.2164 | 0.9943 | 152 | 1.1504 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |