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--- |
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base_model: TinyLlama/TinyLlama_v1.1 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- unsloth |
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- generated_from_trainer |
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model-index: |
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- name: tinyllama_magiccoder_default |
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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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# tinyllama_magiccoder_default |
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This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co/TinyLlama/TinyLlama_v1.1) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4775 |
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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_ratio: 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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| 1.8283 | 0.0262 | 4 | 1.9099 | |
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| 1.8156 | 0.0523 | 8 | 1.8872 | |
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| 1.7063 | 0.0785 | 12 | 1.8112 | |
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| 1.591 | 0.1047 | 16 | 1.6729 | |
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| 1.5878 | 0.1308 | 20 | 1.6188 | |
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| 1.5204 | 0.1570 | 24 | 1.6055 | |
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| 1.5278 | 0.1832 | 28 | 1.6151 | |
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| 1.6098 | 0.2093 | 32 | 1.6174 | |
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| 1.5112 | 0.2355 | 36 | 1.5811 | |
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| 1.6158 | 0.2617 | 40 | 1.5749 | |
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| 1.5373 | 0.2878 | 44 | 1.5431 | |
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| 1.5924 | 0.3140 | 48 | 1.5410 | |
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| 1.5528 | 0.3401 | 52 | 1.5142 | |
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| 1.5049 | 0.3663 | 56 | 1.5183 | |
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| 1.5983 | 0.3925 | 60 | 1.5109 | |
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| 1.5452 | 0.4186 | 64 | 1.5045 | |
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| 1.4746 | 0.4448 | 68 | 1.4973 | |
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| 1.4949 | 0.4710 | 72 | 1.4907 | |
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| 1.451 | 0.4971 | 76 | 1.4963 | |
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| 1.5701 | 0.5233 | 80 | 1.4952 | |
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| 1.5791 | 0.5495 | 84 | 1.4858 | |
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| 1.484 | 0.5756 | 88 | 1.4869 | |
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| 1.4175 | 0.6018 | 92 | 1.4846 | |
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| 1.4127 | 0.6280 | 96 | 1.4826 | |
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| 1.4919 | 0.6541 | 100 | 1.4814 | |
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| 1.4907 | 0.6803 | 104 | 1.4830 | |
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| 1.4656 | 0.7065 | 108 | 1.4812 | |
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| 1.4957 | 0.7326 | 112 | 1.4795 | |
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| 1.4742 | 0.7588 | 116 | 1.4785 | |
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| 1.4694 | 0.7850 | 120 | 1.4759 | |
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| 1.5036 | 0.8111 | 124 | 1.4754 | |
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| 1.4752 | 0.8373 | 128 | 1.4762 | |
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| 1.3607 | 0.8635 | 132 | 1.4766 | |
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| 1.5251 | 0.8896 | 136 | 1.4768 | |
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| 1.3971 | 0.9158 | 140 | 1.4773 | |
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| 1.4457 | 0.9419 | 144 | 1.4771 | |
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| 1.4743 | 0.9681 | 148 | 1.4769 | |
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| 1.4915 | 0.9943 | 152 | 1.4775 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
