rti-formatter – AI Model by CaseLoop | AlphaNeural AI

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CaseLoop/
rti-formatter

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text2text-generation

generated_from_trainer

google/flan-t5-small

text-generation-inference

endpoints_compatible

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rti-formatter

This model is a fine-tuned version of google/flan-t5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0075

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
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: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
0.0701	1.0	57	0.0314
0.0238	2.0	114	0.0156
0.0156	3.0	171	0.0108
0.0130	4.0	228	0.0107
0.0126	5.0	285	0.0089
0.0113	6.0	342	0.0082
0.0117	7.0	399	0.0089
0.0092	8.0	456	0.0078
0.0102	9.0	513	0.0074
0.0089	10.0	570	0.0075

Framework versions

Transformers 5.15.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2