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README.md ADDED
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+ ---
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+ base_model: mistralai/Mistral-7B-Instruct-v0.3
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+ library_name: peft
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+ license: apache-2.0
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ model-index:
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+ - name: Mistral-7B_task-2_60-samples_config-1_auto
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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_task-2_60-samples_config-1_auto
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8507
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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: 0.0001
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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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+ - distributed_type: multi-GPU
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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: 50
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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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+ | 0.7334 | 0.8696 | 5 | 0.7063 |
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+ | 0.6319 | 1.9130 | 11 | 0.5730 |
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+ | 0.5266 | 2.9565 | 17 | 0.5148 |
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+ | 0.4086 | 4.0 | 23 | 0.4890 |
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+ | 0.307 | 4.8696 | 28 | 0.4861 |
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+ | 0.2061 | 5.9130 | 34 | 0.5480 |
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+ | 0.1025 | 6.9565 | 40 | 0.6544 |
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+ | 0.0474 | 8.0 | 46 | 0.7597 |
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+ | 0.0255 | 8.8696 | 51 | 0.7984 |
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+ | 0.0223 | 9.9130 | 57 | 0.7589 |
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+ | 0.0134 | 10.9565 | 63 | 0.8149 |
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+ | 0.0068 | 12.0 | 69 | 0.8507 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.44.0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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