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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_reverse |
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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_reverse |
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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: 1.4617 |
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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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| 1.7988 | 0.0262 | 4 | 1.8569 | |
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| 1.6885 | 0.0523 | 8 | 1.6512 | |
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| 1.5697 | 0.0785 | 12 | 1.6180 | |
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| 1.501 | 0.1047 | 16 | 1.5781 | |
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| 1.5529 | 0.1308 | 20 | 1.5673 | |
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| 1.4779 | 0.1570 | 24 | 1.5470 | |
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| 1.4724 | 0.1832 | 28 | 1.5328 | |
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| 1.5236 | 0.2093 | 32 | 1.5227 | |
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| 1.4405 | 0.2355 | 36 | 1.5105 | |
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| 1.5416 | 0.2617 | 40 | 1.5137 | |
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| 1.4954 | 0.2878 | 44 | 1.5066 | |
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| 1.5539 | 0.3140 | 48 | 1.4984 | |
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| 1.5253 | 0.3401 | 52 | 1.4869 | |
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| 1.4786 | 0.3663 | 56 | 1.4841 | |
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| 1.5582 | 0.3925 | 60 | 1.4856 | |
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| 1.5277 | 0.4186 | 64 | 1.4862 | |
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| 1.4553 | 0.4448 | 68 | 1.4852 | |
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| 1.472 | 0.4710 | 72 | 1.4787 | |
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| 1.4282 | 0.4971 | 76 | 1.4765 | |
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| 1.5454 | 0.5233 | 80 | 1.4738 | |
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| 1.5619 | 0.5495 | 84 | 1.4789 | |
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| 1.4621 | 0.5756 | 88 | 1.4715 | |
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| 1.3989 | 0.6018 | 92 | 1.4703 | |
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| 1.3913 | 0.6280 | 96 | 1.4723 | |
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| 1.4797 | 0.6541 | 100 | 1.4636 | |
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| 1.4766 | 0.6803 | 104 | 1.4707 | |
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| 1.4478 | 0.7065 | 108 | 1.4650 | |
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| 1.4769 | 0.7326 | 112 | 1.4658 | |
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| 1.4517 | 0.7588 | 116 | 1.4650 | |
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| 1.4475 | 0.7850 | 120 | 1.4601 | |
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| 1.4842 | 0.8111 | 124 | 1.4645 | |
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| 1.4513 | 0.8373 | 128 | 1.4625 | |
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| 1.3405 | 0.8635 | 132 | 1.4614 | |
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| 1.5064 | 0.8896 | 136 | 1.4625 | |
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| 1.3767 | 0.9158 | 140 | 1.4628 | |
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| 1.429 | 0.9419 | 144 | 1.4623 | |
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| 1.4623 | 0.9681 | 148 | 1.4619 | |
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| 1.4592 | 0.9943 | 152 | 1.4617 | |
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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 |
