flan-t5-rouge-durga-q5-clean-4c

devagonal/flan-t5-rouge-durga-q5-clean-4c

flan-t5-rouge-durga-q5-clean-4c is a machine learning model from devagonal. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Oct 28, 2024
Updated: Oct 28, 2024
SHA: 7f1c5a27

Base models

google/flan-t5-base

Spaces

devagonal/flan-t5-rouge-durga-q5-clean-4c-space

Model card

From the Hugging Face model README

flan-t5-rouge-durga-q5-clean-4c

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

Loss: 0.2052
Rouge1: 0.4357
Rouge2: 0.2982
Rougel: 0.4326
Rougelsum: 0.4327

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: 24
eval_batch_size: 24
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.438	1.0	9	1.9807	0.2583	0.0732	0.2536	0.2534
2.6463	2.0	18	1.7018	0.2588	0.0705	0.2521	0.2525
1.7877	3.0	27	1.4796	0.2840	0.0824	0.2764	0.2765
2.0417	4.0	36	1.3040	0.3100	0.1072	0.3028	0.3027
2.0216	5.0	45	1.1630	0.3322	0.1262	0.3255	0.3246
1.7093	6.0	54	1.0289	0.3359	0.1283	0.3283	0.3285
1.6109	7.0	63	0.9288	0.3728	0.1752	0.3631	0.3628
1.3041	8.0	72	0.8358	0.3691	0.1709	0.3592	0.3593
1.3242	9.0	81	0.7609	0.3666	0.1744	0.3573	0.3579
1.0971	10.0	90	0.6803	0.3724	0.1809	0.3659	0.3663
0.7156	11.0	99	0.6153	0.3742	0.1833	0.3634	0.3637
0.8419	12.0	108	0.5537	0.3748	0.1870	0.3645	0.3655
0.8853	13.0	117	0.5012	0.3775	0.1986	0.3681	0.3687
1.0922	14.0	126	0.4396	0.3738	0.1960	0.3629	0.3634
0.8752	15.0	135	0.4022	0.3844	0.2097	0.3755	0.3762
0.8189	16.0	144	0.3810	0.4050	0.2350	0.3970	0.3975
0.639	17.0	153	0.3503	0.4039	0.2341	0.3977	0.3976
0.7971	18.0	162	0.3162	0.4082	0.2428	0.4022	0.4028
0.7211	19.0	171	0.3069	0.4174	0.2504	0.4131	0.4128
0.7633	20.0	180	0.2804	0.4204	0.2562	0.4154	0.4167
0.6475	21.0	189	0.2685	0.4308	0.2750	0.4269	0.4274
0.5642	22.0	198	0.2498	0.4232	0.2700	0.4175	0.4184
0.66	23.0	207	0.2377	0.4311	0.2832	0.4246	0.4249
0.6004	24.0	216	0.2335	0.4298	0.2868	0.4255	0.4257
0.6263	25.0	225	0.2216	0.4252	0.2806	0.4211	0.4212
0.4931	26.0	234	0.2146	0.4274	0.2858	0.4232	0.4236
0.5072	27.0	243	0.2091	0.4309	0.2862	0.4266	0.4267
0.5079	28.0	252	0.2069	0.4354	0.2969	0.4315	0.4324
0.494	29.0	261	0.2058	0.4326	0.2965	0.4290	0.4299
0.6008	30.0	270	0.2052	0.4357	0.2982	0.4326	0.4327

Framework versions

Transformers 4.46.0
Pytorch 2.5.0+cu121
Datasets 3.0.2
Tokenizers 0.20.1

Library: transformers
Type: t5
License: apache-2.0
Created: Oct 28, 2024
Updated: Oct 28, 2024