|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- unsloth |
|
- generated_from_trainer |
|
base_model: Qwen/Qwen2-7B |
|
model-index: |
|
- name: qwen2_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. --> |
|
|
|
# qwen2_Magiccoder_evol_10k_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: 0.8039 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 32 |
|
- 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 | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.8045 | 0.0261 | 4 | 0.8796 | |
|
| 0.8394 | 0.0522 | 8 | 0.8315 | |
|
| 0.8027 | 0.0784 | 12 | 0.8188 | |
|
| 0.7742 | 0.1045 | 16 | 0.8136 | |
|
| 0.8206 | 0.1306 | 20 | 0.8118 | |
|
| 0.7117 | 0.1567 | 24 | 0.8110 | |
|
| 0.7248 | 0.1828 | 28 | 0.8097 | |
|
| 0.893 | 0.2089 | 32 | 0.8113 | |
|
| 0.7788 | 0.2351 | 36 | 0.8096 | |
|
| 0.8043 | 0.2612 | 40 | 0.8098 | |
|
| 0.8427 | 0.2873 | 44 | 0.8108 | |
|
| 0.8171 | 0.3134 | 48 | 0.8098 | |
|
| 0.7509 | 0.3395 | 52 | 0.8103 | |
|
| 0.7373 | 0.3656 | 56 | 0.8105 | |
|
| 0.7708 | 0.3918 | 60 | 0.8107 | |
|
| 0.7942 | 0.4179 | 64 | 0.8109 | |
|
| 0.8188 | 0.4440 | 68 | 0.8103 | |
|
| 0.768 | 0.4701 | 72 | 0.8100 | |
|
| 0.786 | 0.4962 | 76 | 0.8095 | |
|
| 0.7728 | 0.5223 | 80 | 0.8094 | |
|
| 0.8575 | 0.5485 | 84 | 0.8091 | |
|
| 0.7635 | 0.5746 | 88 | 0.8088 | |
|
| 0.8469 | 0.6007 | 92 | 0.8082 | |
|
| 0.7647 | 0.6268 | 96 | 0.8078 | |
|
| 0.8741 | 0.6529 | 100 | 0.8073 | |
|
| 0.7574 | 0.6790 | 104 | 0.8067 | |
|
| 0.8048 | 0.7052 | 108 | 0.8061 | |
|
| 0.7615 | 0.7313 | 112 | 0.8056 | |
|
| 0.7452 | 0.7574 | 116 | 0.8051 | |
|
| 0.7191 | 0.7835 | 120 | 0.8049 | |
|
| 0.7999 | 0.8096 | 124 | 0.8046 | |
|
| 0.7317 | 0.8357 | 128 | 0.8045 | |
|
| 0.8619 | 0.8619 | 132 | 0.8044 | |
|
| 0.8071 | 0.8880 | 136 | 0.8040 | |
|
| 0.8034 | 0.9141 | 140 | 0.8040 | |
|
| 0.7892 | 0.9402 | 144 | 0.8040 | |
|
| 0.8291 | 0.9663 | 148 | 0.8040 | |
|
| 0.7938 | 0.9925 | 152 | 0.8039 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.7.1 |
|
- Transformers 4.40.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
