information-extraction-llama3-8B-4bit-finetuned

Model Card for Model ID

The model extracts the triplet from the given text. Example: Input: "Nie Haisheng, born on October 13, 1964, worked as a fighter pilot." Output: {'mtriple_set': [['Nie_Haisheng | birthDate | 1964-10-13', 'Nie_Haisheng | occupation | Fighter_pilot']]}

Model Details

Base Model: Llama 3 - 8B Qunatisation: 4 bit LoRA rank: 16

Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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Uses

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Direct Use

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How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

• Training regime:

  trainer = SFTTrainer(
    model = model,
     tokenizer = tokenizer,
     train_dataset = train,
     dataset_text_field = "text",
     max_seq_length = max_seq_length,
     dataset_num_proc = 2,
     packing = False, # Can make training 5x faster for short sequences.
     args = TrainingArguments(
         per_device_train_batch_size = 2,
         gradient_accumulation_steps = 4,
         warmup_steps = 5,
         max_steps = 50,
         learning_rate = 2e-4,
         fp16 = not is_bfloat16_supported(),
         bf16 = is_bfloat16_supported(),
         logging_steps = 1,
         optim = "adamw_8bit",
         weight_decay = 0.01,
         lr_scheduler_type = "linear",
         seed = 3407,
         output_dir = "outputs",
    ),
)```
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## Evaluation

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### Results

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#### Summary



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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** 1 T4 GPU, RAM: 16 GB
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- **Cloud Provider:** Google CoLab
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## Technical Specifications [optional]

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## Citation [optional]

https://colab.research.google.com/drive/135ced7oHytdxu3N2DNe1Z0kqjyYIkDXp?usp=sharing#scrollTo=kR3gIAX-SM2q

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