best-echelon-model – AI Model by aminLo | AlphaNeural AI

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best-echelon-model

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google/flan-t5-base

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best-echelon-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: 0.2217

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: 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: 8

Training results

Training Loss	Epoch	Step	Validation Loss
0.2963	0.9627	200	0.3645
0.1886	1.9242	400	0.2526
0.1497	2.8857	600	0.2311
0.1383	3.8472	800	0.2511
0.1476	4.8087	1000	0.2393
0.1341	5.7702	1200	0.2286
0.1288	6.7316	1400	0.2195
0.1085	7.6931	1600	0.2217

Framework versions

PEFT 0.17.1
Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0