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End of training

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README.md ADDED
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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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+
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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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+
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+ # tinyllama_magiccoder_default
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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
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