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llama-lora-Paiwan-summarization – AI Model by aslinguist | AlphaNeural AI
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llama-lora-Paiwan-summarization
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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-lora-Paiwan-summarization
This model is a fine-tuned version of
meta-llama/Llama-3.1-8B-Instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.8863
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: 0.001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
9
3.1561
3.4715
2.0
18
2.9315
2.886
3.0
27
2.7974
2.5873
4.0
36
2.7141
2.3277
5.0
45
2.6736
2.1141
6.0
54
2.6551
1.8659
7.0
63
2.7040
1.6632
8.0
72
2.7634
1.4296
9.0
81
2.8863
Framework versions
PEFT 0.15.0
Transformers 4.51.2
Pytorch 2.2.2+cu118
Datasets 3.5.0
Tokenizers 0.21.1
