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Amala3
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IronyExplainer_mixed

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sft
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PEFT library
# Gated model: Login with a HF token with gated access permission
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from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-70B-Instruct")
model = PeftModel.from_pretrained(base_model, "Amala3/IronyExplainer_mixed")

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output_Meta-Llama-3-70B-Instruct_explainer_mixed

This model is a fine-tuned version of meta-llama/Meta-Llama-3-70B-Instruct on the None dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.2
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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meta-llama/Meta-Llama-3-70B
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