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JudicialSummarization-FinetuneLlama3.18b – AI Model by Hiranmai49 | AlphaNeural AI
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JudicialSummarization-FinetuneLlama3.18b
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peft
safetensors
generated_from_trainer
meta-llama/Llama-3.1-8B-Instruct
adapter
llama3.1
us
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Llama-3.1-8B-Instruct-JudicialSummarization-FinetuneLlama3.18b
This model is a fine-tuned version of
meta-llama/Llama-3.1-8B-Instruct
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 6.4096
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: 2.5e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 5
training_steps: 2000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
6.4708
0.6887
500
6.4666
6.4187
1.3774
1000
6.4331
6.3747
2.0661
1500
6.4159
6.3408
2.7548
2000
6.4096
Framework versions
PEFT 0.13.2
Transformers 4.46.1
Pytorch 2.4.0+cu121
Datasets 3.0.1
Tokenizers 0.20.1
