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results – AI Model by Tessava | AlphaNeural AI | AlphaNeural AI
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Tessava
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results
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peft
safetensors
generated_from_trainer
meta-llama/Llama-3.2-1B-Instruct
adapter
llama3.2
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This model is a fine-tuned version of
meta-llama/Llama-3.2-1B-Instruct
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6051
Accuracy: 0.6855
F1: 0.6593
Precision: 0.6361
Recall: 0.6842
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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.586
1.0
1782
0.6051
0.6855
0.6593
0.6361
0.6842
Framework versions
PEFT 0.14.0
Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0
