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llama-3-freeze-full-data – AI Model by tanjumajerin | AlphaNeural AI
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tanjumajerin
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llama-3-freeze-full-data
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peft
safetensors
generated_from_trainer
meta-llama/Meta-Llama-3-8B
adapter
llama3
us
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llama-3-full-data
This model is a fine-tuned version of
meta-llama/Meta-Llama-3-8B
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.1187
Accuracy: 0.5827
F1: 0.5786
Precision: 0.5883
Recall: 0.5827
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.7131
0.9999
5167
1.1500
0.5716
0.5696
0.5746
0.5716
0.5229
1.9999
10335
1.1417
0.5830
0.5754
0.5926
0.5830
0.5
2.9996
15501
1.1187
0.5827
0.5786
0.5883
0.5827
Framework versions
PEFT 0.10.0
Transformers 4.40.0
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.19.1
