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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: halcyon-llm/SmolLM2-360M-japanese_base_phase_1-11000
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - kajuma/training_01-09_token
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+ model-index:
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+ - name: scratch_adamw_phase_2
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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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+ # scratch_adamw_phase_2
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+
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+ This model is a fine-tuned version of [halcyon-llm/SmolLM2-360M-japanese_base_phase_1-11000](https://huggingface.co/halcyon-llm/SmolLM2-360M-japanese_base_phase_1-11000) on the kajuma/training_01-09_token dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1349
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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: 0.003
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 64
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+ - total_train_batch_size: 256
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+ - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine_with_min_lr
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+ - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 1.0
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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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+ | 1.1622 | 0.0438 | 500 | 1.1753 |
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+ | 1.2027 | 0.0877 | 1000 | 1.2353 |
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+ | 1.207 | 0.1315 | 1500 | 1.2419 |
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+ | 1.2536 | 0.1754 | 2000 | 1.2374 |
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+ | 1.2442 | 0.2192 | 2500 | 1.2315 |
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+ | 1.2163 | 0.2631 | 3000 | 1.2262 |
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+ | 1.1969 | 0.3069 | 3500 | 1.2185 |
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+ | 1.2102 | 0.3508 | 4000 | 1.2099 |
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+ | 1.1908 | 0.3946 | 4500 | 1.2016 |
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+ | 1.1611 | 0.4385 | 5000 | 1.1929 |
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+ | 1.2055 | 0.4823 | 5500 | 1.1835 |
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+ | 1.1743 | 0.5262 | 6000 | 1.1750 |
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+ | 1.1519 | 0.5700 | 6500 | 1.1674 |
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+ | 1.1397 | 0.6138 | 7000 | 1.1601 |
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+ | 1.1702 | 0.6577 | 7500 | 1.1538 |
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+ | 1.1633 | 0.7015 | 8000 | 1.1483 |
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+ | 1.1248 | 0.7454 | 8500 | 1.1439 |
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+ | 1.1306 | 0.7892 | 9000 | 1.1407 |
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+ | 1.0726 | 0.8331 | 9500 | 1.1385 |
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+ | 1.1104 | 0.8769 | 10000 | 1.1369 |
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+ | 1.0933 | 0.9208 | 10500 | 1.1359 |
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+ | 1.0918 | 0.9646 | 11000 | 1.1352 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.0.dev0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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+ "eval_samples_per_second": 33.681,
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