T5_Ru_VKR – AI Model by Megnis | AlphaNeural AI

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Megnis/
T5_Ru_VKR

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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T5_Ru_VKR

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

Loss: 1.8474
Rouge1: 0.0229
Rouge2: 0.0135
Rougel: 0.0228
Rougelsum: 0.0227
Gen Len: 18.845

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	100	1.9287	0.0246	0.0135	0.0245	0.0242	18.865
No log	2.0	200	1.8761	0.0213	0.0135	0.0212	0.021	18.845
No log	3.0	300	1.8454	0.0213	0.0135	0.0212	0.021	18.845
No log	4.0	400	1.8474	0.0229	0.0135	0.0228	0.0227	18.845

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.19.1