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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: other
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+ base_model: NousResearch/Meta-Llama-3-8B-Instruct
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+ tags:
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+ - llama-factory
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+ - full
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+ - generated_from_trainer
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+ model-index:
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+ - name: sft
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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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+ # sft
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+
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+ This model is a fine-tuned version of [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) on the identity and the iplaw20241002 datasets.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1582
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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: 1e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 8
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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: 0.1
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+ - num_epochs: 12.0
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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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+ | 0.0713 | 6.8376 | 1000 | 0.1959 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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+ {
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+ "epoch": 11.97948717948718,
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+ "eval_loss": 0.15816539525985718,
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+ "eval_runtime": 5.1001,
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+ "eval_samples_per_second": 25.49,
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+ "eval_steps_per_second": 25.49,
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+ "total_flos": 9.576163802677248e+16,
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+ "train_loss": 0.4554890414942311,
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+ "train_runtime": 1838.2954,
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+ "train_samples_per_second": 7.638,
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+ "train_steps_per_second": 0.953
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+ }
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+ "LlamaForCausalLM"
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