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Llama-2-7b-Summarization-QLoRa – AI Model by pkbiswas | AlphaNeural AI
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pkbiswas
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Llama-2-7b-Summarization-QLoRa
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peft
safetensors
generated_from_trainer
summarization
scitldr
meta-llama/Llama-2-7b-hf
adapter
us
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Llama Summarization
This model is a fine-tuned version of
meta-llama/Llama-2-7b-hf
on the scitldr dataset. It achieves the following results on the evaluation set:
Loss: 2.1108
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: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
2.0965
0.25
500
2.1496
2.0523
0.5
1000
2.1275
2.0824
0.75
1500
2.1108
Framework versions
PEFT 0.9.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
