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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: mistralai/Mistral-7B-Instruct-v0.1
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: mistral-try-finetune
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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-try-finetune
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3805
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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: 2.5e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 8
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+ - seed: 18
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+ - gradient_accumulation_steps: 4
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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: constant
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+ - lr_scheduler_warmup_steps: 5
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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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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+ | 1.5606 | 0.57 | 50 | 0.8581 |
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+ | 0.5656 | 1.14 | 100 | 0.5153 |
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+ | 0.3651 | 1.71 | 150 | 0.4257 |
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+ | 0.2995 | 2.29 | 200 | 0.3750 |
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+ | 0.2008 | 2.86 | 250 | 0.3405 |
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+ | 0.1693 | 3.43 | 300 | 0.3282 |
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+ | 0.144 | 4.0 | 350 | 0.3156 |
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+ | 0.1112 | 4.57 | 400 | 0.3209 |
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+ | 0.0949 | 5.14 | 450 | 0.3346 |
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+ | 0.0801 | 5.71 | 500 | 0.3212 |
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+ | 0.0717 | 6.29 | 550 | 0.3288 |
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+ | 0.0579 | 6.86 | 600 | 0.3255 |
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+ | 0.0486 | 7.43 | 650 | 0.3359 |
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+ | 0.0495 | 8.0 | 700 | 0.3273 |
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+ | 0.0374 | 8.57 | 750 | 0.3617 |
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+ | 0.0377 | 9.14 | 800 | 0.3725 |
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+ | 0.0324 | 9.71 | 850 | 0.3697 |
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+ | 0.0338 | 10.29 | 900 | 0.3946 |
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+ | 0.0305 | 10.86 | 950 | 0.3605 |
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+ | 0.0289 | 11.43 | 1000 | 0.3805 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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+ {
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+ "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.1",
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "lora_dropout": 0.05,
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+ "lm_head",
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+ "q_proj"
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+ ],
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+ "task_type": "CAUSAL_LM"
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+ }
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