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---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: Qwen/Qwen2-7B
model-index:
- name: qwen2_Magiccoder_evol_10k_qlora_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. -->
# qwen2_Magiccoder_evol_10k_qlora_ortho
This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9025
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8992 | 0.0261 | 4 | 0.9547 |
| 0.9045 | 0.0522 | 8 | 0.9234 |
| 0.9145 | 0.0783 | 12 | 0.9166 |
| 0.8688 | 0.1044 | 16 | 0.9117 |
| 0.9222 | 0.1305 | 20 | 0.9097 |
| 0.8108 | 0.1566 | 24 | 0.9090 |
| 0.8194 | 0.1827 | 28 | 0.9083 |
| 0.9616 | 0.2088 | 32 | 0.9086 |
| 0.8624 | 0.2349 | 36 | 0.9083 |
| 0.8898 | 0.2610 | 40 | 0.9088 |
| 0.9476 | 0.2871 | 44 | 0.9085 |
| 0.9156 | 0.3132 | 48 | 0.9091 |
| 0.8388 | 0.3393 | 52 | 0.9091 |
| 0.8429 | 0.3654 | 56 | 0.9087 |
| 0.8651 | 0.3915 | 60 | 0.9081 |
| 0.9228 | 0.4176 | 64 | 0.9082 |
| 0.9167 | 0.4437 | 68 | 0.9076 |
| 0.8769 | 0.4698 | 72 | 0.9068 |
| 0.9009 | 0.4959 | 76 | 0.9069 |
| 0.8611 | 0.5220 | 80 | 0.9074 |
| 0.9496 | 0.5481 | 84 | 0.9070 |
| 0.8562 | 0.5742 | 88 | 0.9067 |
| 0.943 | 0.6003 | 92 | 0.9060 |
| 0.8718 | 0.6264 | 96 | 0.9053 |
| 0.9642 | 0.6525 | 100 | 0.9046 |
| 0.8425 | 0.6786 | 104 | 0.9042 |
| 0.886 | 0.7047 | 108 | 0.9040 |
| 0.8576 | 0.7308 | 112 | 0.9043 |
| 0.823 | 0.7569 | 116 | 0.9036 |
| 0.8158 | 0.7830 | 120 | 0.9032 |
| 0.8854 | 0.8091 | 124 | 0.9031 |
| 0.8502 | 0.8352 | 128 | 0.9030 |
| 0.9493 | 0.8613 | 132 | 0.9026 |
| 0.8934 | 0.8874 | 136 | 0.9026 |
| 0.9158 | 0.9135 | 140 | 0.9026 |
| 0.8686 | 0.9396 | 144 | 0.9026 |
| 0.9321 | 0.9657 | 148 | 0.9027 |
| 0.8882 | 0.9918 | 152 | 0.9025 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |