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debug_test – AI Model by mtzig | AlphaNeural AI
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mtzig
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debug_test
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peft
safetensors
llama
generated_from_trainer
TinyPixel/small-llama2
adapter
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debug_test
This model is a fine-tuned version of
TinyPixel/small-llama2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7894
Accuracy: 0.4982
Precision: 0.3939
Recall: 0.7114
F1: 0.5071
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
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 32
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.8214
1.0
5
0.7894
0.4982
0.3939
0.7114
0.5071
Framework versions
PEFT 0.13.2
Transformers 4.46.0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3
