This model is a fine-tuned version of google-t5/t5-small on the govreport-summarization dataset. It achieves the following results on the evaluation set:

Loss: 3.8367
Rouge1: 0.0371
Rouge2: 0.0142
Rougel: 0.0316
Rougelsum: 0.0352

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
19.9287	0.99	31	11.5775	0.0331	0.0151	0.0293	0.0317
12.489	1.98	62	9.1322	0.0373	0.0162	0.0322	0.0351
10.8693	2.98	93	7.8834	0.0367	0.0153	0.0327	0.0348
9.1603	4.0	125	6.8580	0.0374	0.0162	0.0322	0.0355
8.2587	4.99	156	5.7038	0.0382	0.0154	0.0326	0.0366
6.6869	5.98	187	4.8553	0.0388	0.0159	0.0341	0.037
5.8997	6.98	218	4.3049	0.0383	0.0145	0.0336	0.036
5.0285	8.0	250	3.9143	0.0369	0.0138	0.0311	0.035
4.5944	8.99	281	3.8533	0.0376	0.0149	0.032	0.0353
4.5239	9.92	310	3.8367	0.0371	0.0142	0.0316	0.0352

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1

RMWeerasinghe/t5-small-finetuned-govReport-3072

t5-small-finetuned-govReport-3072

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RMWeerasinghe/
t5-small-finetuned-govReport-3072