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tigerbhai/mistral-texmin

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: mistralai/Mistral-7B-Instruct-v0.1
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+ model-index:
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+ - name: mistral_texmin
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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_texmin
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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: 0.0292
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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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+
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+ The following `bitsandbytes` quantization config was used during training:
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+ - quant_method: bitsandbytes
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+ - load_in_8bit: False
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+ - load_in_4bit: True
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+ - llm_int8_threshold: 6.0
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+ - llm_int8_skip_modules: None
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+ - llm_int8_enable_fp32_cpu_offload: False
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+ - llm_int8_has_fp16_weight: False
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+ - bnb_4bit_quant_type: nf4
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+ - bnb_4bit_use_double_quant: True
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+ - bnb_4bit_compute_dtype: bfloat16
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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: 0.0002
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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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: 0.03
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+ - training_steps: 100
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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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+ | 0.6494 | 0.62 | 20 | 0.4569 |
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+ | 0.3477 | 1.25 | 40 | 0.1761 |
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+ | 0.1239 | 1.88 | 60 | 0.0429 |
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+ | 0.0443 | 2.5 | 80 | 0.0345 |
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+ | 0.034 | 3.12 | 100 | 0.0292 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.7.0
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+ - Transformers 4.36.0
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+ - Pytorch 2.1.1+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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