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fine-tuned-llama-3-coaid – AI Model by tanjumajerin | AlphaNeural AI
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tanjumajerin
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fine-tuned-llama-3-coaid
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peft
safetensors
generated_from_trainer
meta-llama/Meta-Llama-3-8B
adapter
llama3
us
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fine-tuned-llama-3-coaid
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: 0.2869
Accuracy: 0.9159
F1: 0.9103
Precision: 0.9099
Recall: 0.9159
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: 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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.314
1.0
47
0.3207
0.9065
0.9003
0.8991
0.9065
0.1965
2.0
94
0.2869
0.9159
0.9103
0.9099
0.9159
Framework versions
PEFT 0.10.0
Transformers 4.40.0
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.19.1
