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README.md ADDED
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+ ---
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+ base_model: checkpoints/Mistral-7B-Instruct-EI-Iter2
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+ datasets:
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+ - synthetic_data_mistral-7b-instruct-expert-iteration-iter3_score
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+ tags:
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+ - alignment-handbook
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+ - generated_from_trainer
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+ - autoquant
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+ - gptq
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+ model-index:
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+ - name: Mistral-7B-Instruct-EI-Iter3
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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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+ # Mistral-7B-Instruct-EI-Iter3
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+
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+ This model is a fine-tuned version of [checkpoints/Mistral-7B-Instruct-EI-Iter2](https://huggingface.co/checkpoints/Mistral-7B-Instruct-EI-Iter2) on the synthetic_data_mistral-7b-instruct-expert-iteration-iter3_score dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4722
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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: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - total_train_batch_size: 64
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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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+ - lr_scheduler_warmup_ratio: 0.1
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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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+ | 0.6652 | 1.0 | 106 | 0.4722 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.19.1
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+ "_name_or_path": "UCLAML/mistral-7b-expert-iteration-iter3",
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+ ],
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+ "num_hidden_layers": 32,
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+ "quantization_config": {
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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