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README.md
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---
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library_name: peft
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---
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Framework versions
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-
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---
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library_name: peft
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datasets:
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- ChristophSchuhmann/essays-with-instructions
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language:
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- en
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metrics:
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- perplexity
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---
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Model Description
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For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/OPT%20Models/Essays%20With%20Instructions%20-%20Fine-Tune%20-%20OPT.ipynb
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### Intended uses & limitations
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This is intended to show the possibilities. It is mainly limited by the input data.
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### Training & Evaluation Dataset
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Dataset Source: https://huggingface.co/datasets/ChristophSchuhmann/essays-with-instructions
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### Hyperparameters Used
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| Hyperperameter | Value |
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|:-----:|:-----:|
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| Model Checkpoint | facebook/opt-2.7b |
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| per_device_train_batch_size | 8 |
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| gradient_accumulation_steps | 4 |
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| fp16 | True |
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| warmup_steps | 75 |
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| learning_rate | 2e-4 |
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| Training Steps | 150 |
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### Framework versions
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| Library | Version |
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|:-----:|:-----:|
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| Python | 3.10.1 |
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| Torch | 2.0.1+cu118 |
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| Datasets | 2.14.4 |
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| Transformer | 4.31.0 |
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| PEFT | 0.4.0 |
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### Metric
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Perplexity = 9.46
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