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contemmcm/
607ae8b49d7e6f769645de3b50e62736

generated_from_trainer

albert/albert-large-v2

finetune

apache-2.0

endpoints_compatible

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607ae8b49d7e6f769645de3b50e62736

This model is a fine-tuned version of albert/albert-large-v2 on the fancyzhx/dbpedia_14 dataset. It achieves the following results on the evaluation set:

Loss: 2.6485
Data Size: 1.0
Epoch Runtime: 1178.9986
Accuracy: 0.0712
F1 Macro: 0.0095
Rouge1: 0.0712
Rouge2: 0.0
Rougel: 0.0712
Rougelsum: 0.0712

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro	Rouge1	Rougel	Rougelsum
No log	0	0	2.7614	0	43.6068	0.0717	0.0102	0.0718	0.0717	0.0717
2.664	1	17500	2.6674	0.0078	54.0667	0.0681	0.0109	0.0681	0.0682	0.0681
2.6682	2	35000	2.6563	0.0156	61.6015	0.0714	0.0095	0.0714	0.0715	0.0715
2.596	3	52500	2.3102	0.0312	78.5183	0.1406	0.0548	0.1407	0.1405	0.1407
2.2545	4	70000	2.2548	0.0625	113.1290	0.1409	0.0516	0.1409	0.1409	0.1410
2.6494	5	87500	2.7364	0.125	185.1481	0.0638	0.0308	0.0638	0.0638	0.0638
2.3837	6	105000	2.4101	0.25	329.9255	0.1358	0.0504	0.1357	0.1357	0.1358
0.0138	7	122500	2.4209	0.5	612.2917	0.1387	0.0469	0.1387	0.1387	0.1386
2.6562	8.0	140000	2.6485	1.0	1178.9986	0.0712	0.0095	0.0712	0.0712	0.0712

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.0.0
Tokenizers 0.22.1

contemmcm/607ae8b49d7e6f769645de3b50e62736

607ae8b49d7e6f769645de3b50e62736

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

contemmcm/
607ae8b49d7e6f769645de3b50e62736