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idt5_base-silver-standard-lora – AI Model by Firmansyah-Ibrahim | AlphaNeural AI
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Firmansyah-Ibrahim
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idt5_base-silver-standard-lora
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peft
safetensors
adapter
lora
transformers
muchad/idt5-base
apache-2.0
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idt5_base-silver-standard-lora
This model is a fine-tuned version of
muchad/idt5-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 5.9463
Rouge1: 0.1894
Rouge2: 0.0
Rougel: 0.1968
Rougelsum: 0.1866
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: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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
Rouge1
Rouge2
Rougel
Rougelsum
39.0609
1.0
149
7.6769
6.1515
0.1684
6.1419
6.1546
30.7822
2.0
298
6.1796
0.7179
0.0
0.7313
0.7174
28.7988
3.0
447
5.9463
0.1894
0.0
0.1968
0.1866
Framework versions
PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
