File size: 3,394 Bytes
8e131cf b96553c 8e131cf b96553c 8e131cf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 |
---
base_model: unsloth/qwen2-7b-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_magiccoder_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. -->
# Qwen2-7B_magiccoder_reverse
This model is a fine-tuned version of [unsloth/qwen2-7b-bnb-4bit](https://huggingface.co./unsloth/qwen2-7b-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0421
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9108 | 0.0261 | 4 | 0.9707 |
| 0.9882 | 0.0522 | 8 | 1.0348 |
| 1.0325 | 0.0783 | 12 | 1.0383 |
| 1.0044 | 0.1044 | 16 | 1.0488 |
| 1.0614 | 0.1305 | 20 | 1.0597 |
| 0.9711 | 0.1566 | 24 | 1.0676 |
| 0.979 | 0.1827 | 28 | 1.0751 |
| 1.1009 | 0.2088 | 32 | 1.0812 |
| 1.014 | 0.2349 | 36 | 1.0818 |
| 1.057 | 0.2610 | 40 | 1.0841 |
| 1.1137 | 0.2871 | 44 | 1.0848 |
| 1.0856 | 0.3132 | 48 | 1.0879 |
| 1.0044 | 0.3393 | 52 | 1.0875 |
| 1.0199 | 0.3654 | 56 | 1.0862 |
| 1.0503 | 0.3915 | 60 | 1.0861 |
| 1.0973 | 0.4176 | 64 | 1.0831 |
| 1.0846 | 0.4437 | 68 | 1.0824 |
| 1.051 | 0.4698 | 72 | 1.0805 |
| 1.0629 | 0.4959 | 76 | 1.0797 |
| 1.0294 | 0.5220 | 80 | 1.0759 |
| 1.0989 | 0.5481 | 84 | 1.0724 |
| 1.0112 | 0.5742 | 88 | 1.0708 |
| 1.0885 | 0.6003 | 92 | 1.0696 |
| 1.0212 | 0.6264 | 96 | 1.0651 |
| 1.1114 | 0.6525 | 100 | 1.0617 |
| 0.994 | 0.6786 | 104 | 1.0602 |
| 1.0346 | 0.7047 | 108 | 1.0566 |
| 1.0053 | 0.7308 | 112 | 1.0539 |
| 0.9673 | 0.7569 | 116 | 1.0506 |
| 0.9526 | 0.7830 | 120 | 1.0489 |
| 1.0196 | 0.8091 | 124 | 1.0475 |
| 1.0054 | 0.8352 | 128 | 1.0456 |
| 1.0743 | 0.8613 | 132 | 1.0439 |
| 1.011 | 0.8874 | 136 | 1.0430 |
| 1.0417 | 0.9135 | 140 | 1.0426 |
| 0.9953 | 0.9396 | 144 | 1.0422 |
| 1.0592 | 0.9657 | 148 | 1.0420 |
| 1.019 | 0.9918 | 152 | 1.0421 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |