flan-t5-small-compression-v2 – AI Model by dotslashderek | AlphaNeural AI

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flan-t5-small-compression-v2

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text2text-generation

generated_from_trainer

google/flan-t5-small

text-generation-inference

endpoints_compatible

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flan-t5-small-compression

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: 0.5181
Rouge1: 0.8820
Rouge2: 0.7104
Rougel: 0.8485
Rougelsum: 0.8488
Comp Ratio Mean: 0.6611
Comp Ratio P90: 0.7674
Pct Violations: 0.0

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adafactor and the args are: No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Comp Ratio Mean	Comp Ratio P90	Pct Violations
1.2576	1.0	1594	0.6457	0.8528	0.6587	0.8197	0.8199	0.6626	0.7736	0.0
0.7688	2.0	3188	0.5727	0.8689	0.6851	0.8345	0.8349	0.6647	0.7694	0.0
0.6591	3.0	4782	0.5405	0.8750	0.6963	0.8413	0.8417	0.6684	0.7692	0.0
0.5957	4.0	6376	0.5333	0.8771	0.7002	0.8438	0.8440	0.6600	0.7660	0.0
0.548	5.0	7970	0.5212	0.8792	0.7059	0.8467	0.8470	0.6617	0.7648	0.0004
0.5139	6.0	9564	0.5196	0.8799	0.7064	0.8472	0.8473	0.6597	0.7636	0.0
0.4862	7.0	11158	0.5144	0.8805	0.7076	0.8473	0.8474	0.6656	0.7705	0.0004
0.466	8.0	12752	0.5157	0.8819	0.7098	0.8489	0.8492	0.6622	0.7674	0.0
0.4499	9.0	14346	0.5156	0.8816	0.7096	0.8486	0.8489	0.6604	0.7660	0.0
0.4393	10.0	15940	0.5181	0.8820	0.7104	0.8485	0.8488	0.6611	0.7674	0.0

Framework versions

Transformers 4.57.1
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.22.1