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best-date-model – AI Model by aminLo | AlphaNeural AI
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best-date-model
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peft
tensorboard
safetensors
adapter
lora
transformers
google/flan-t5-base
apache-2.0
us
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best-Date-model
This model is a fine-tuned version of
google/flan-t5-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0416
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: 0.0004
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.05
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
0.1885
0.7921
200
0.0803
0.1378
1.5822
400
0.0663
0.0717
2.3723
600
0.0491
0.0664
3.1624
800
0.0425
0.03
3.9545
1000
0.0424
0.0456
4.7446
1200
0.0425
0.0295
5.5347
1400
0.0416
Framework versions
PEFT 0.17.1
Transformers 4.56.2
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
