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README.md ADDED
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+ ---
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+ base_model: meta-llama/Llama-2-7b-hf
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+ tags:
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+ - alignment-handbook
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+ - generated_from_trainer
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+ datasets:
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+ - HuggingFaceH4/ultrachat_200k
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+ model-index:
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+ - name: Llama-2-7b-hf-sft-full-gpu4
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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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+ # Llama-2-7b-hf-sft-full-gpu4
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+
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+ This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the HuggingFaceH4/ultrachat_200k dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9378
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 512
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+ - total_eval_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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+ - 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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+ | 0.9338 | 0.7 | 285 | 0.9378 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.14.6
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+ - Tokenizers 0.15.0
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+ {
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+ "epoch": 0.7,
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+ "eval_samples_per_second": 35.254,
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+ "eval_steps_per_second": 0.552,
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+ "train_loss": 0.9589325068289773,
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+ "train_samples": 207865,
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+ "train_samples_per_second": 8.702,
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+ "train_steps_per_second": 0.017
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+ }
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+ {
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+ "_name_or_path": "meta-llama/Llama-2-7b-hf",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "model_type": "llama",
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+ }
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