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FWA_Prediction_Model – AI Model by Chidem | AlphaNeural AI
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Chidem
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FWA_Prediction_Model
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peft
tensorboard
safetensors
unsloth
generated_from_trainer
unsloth/tinyllama-chat-bnb-4bit
adapter
apache-2.0
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FWA_Prediction_Model
This model is a fine-tuned version of
unsloth/tinyllama-chat-bnb-4bit
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.6014
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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.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: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.0587
1.0
603
1.5488
0.0016
2.0
1206
1.5880
0.0017
2.9959
1806
1.6014
Framework versions
PEFT 0.15.2
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
