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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- unsloth |
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- generated_from_trainer |
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base_model: Qwen/Qwen2-7B |
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model-index: |
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- name: qwen2_Magiccoder_evol_10k_qlora_ortho |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# qwen2_Magiccoder_evol_10k_qlora_ortho |
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This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9025 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 0.02 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.8992 | 0.0261 | 4 | 0.9547 | |
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| 0.9045 | 0.0522 | 8 | 0.9234 | |
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| 0.9145 | 0.0783 | 12 | 0.9166 | |
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| 0.8688 | 0.1044 | 16 | 0.9117 | |
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| 0.9222 | 0.1305 | 20 | 0.9097 | |
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| 0.8108 | 0.1566 | 24 | 0.9090 | |
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| 0.8194 | 0.1827 | 28 | 0.9083 | |
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| 0.9616 | 0.2088 | 32 | 0.9086 | |
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| 0.8624 | 0.2349 | 36 | 0.9083 | |
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| 0.8898 | 0.2610 | 40 | 0.9088 | |
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| 0.9476 | 0.2871 | 44 | 0.9085 | |
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| 0.9156 | 0.3132 | 48 | 0.9091 | |
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| 0.8388 | 0.3393 | 52 | 0.9091 | |
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| 0.8429 | 0.3654 | 56 | 0.9087 | |
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| 0.8651 | 0.3915 | 60 | 0.9081 | |
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| 0.9228 | 0.4176 | 64 | 0.9082 | |
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| 0.9167 | 0.4437 | 68 | 0.9076 | |
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| 0.8769 | 0.4698 | 72 | 0.9068 | |
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| 0.9009 | 0.4959 | 76 | 0.9069 | |
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| 0.8611 | 0.5220 | 80 | 0.9074 | |
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| 0.9496 | 0.5481 | 84 | 0.9070 | |
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| 0.8562 | 0.5742 | 88 | 0.9067 | |
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| 0.943 | 0.6003 | 92 | 0.9060 | |
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| 0.8718 | 0.6264 | 96 | 0.9053 | |
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| 0.9642 | 0.6525 | 100 | 0.9046 | |
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| 0.8425 | 0.6786 | 104 | 0.9042 | |
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| 0.886 | 0.7047 | 108 | 0.9040 | |
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| 0.8576 | 0.7308 | 112 | 0.9043 | |
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| 0.823 | 0.7569 | 116 | 0.9036 | |
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| 0.8158 | 0.7830 | 120 | 0.9032 | |
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| 0.8854 | 0.8091 | 124 | 0.9031 | |
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| 0.8502 | 0.8352 | 128 | 0.9030 | |
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| 0.9493 | 0.8613 | 132 | 0.9026 | |
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| 0.8934 | 0.8874 | 136 | 0.9026 | |
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| 0.9158 | 0.9135 | 140 | 0.9026 | |
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| 0.8686 | 0.9396 | 144 | 0.9026 | |
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| 0.9321 | 0.9657 | 148 | 0.9027 | |
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| 0.8882 | 0.9918 | 152 | 0.9025 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
