fine_tuned_t5_small_model_sec_5_v3

miasetya/fine_tuned_t5_small_model_sec_5_v3

fine_tuned_t5_small_model_sec_5_v3 is a machine learning model from miasetya. 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. --

Downloads · 30 days

12% of all-time downloads

All-time downloads

Public

Parameters

60.5M

243 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors242 MB · 100%

At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Dec 4, 2024
Updated: Dec 4, 2024
SHA: 37c83b97

Base models

Model card

From the Hugging Face model README

fine_tuned_t5_small_model_sec_5_v3

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

Loss: 2.8693
Rouge1: 0.3608
Rouge2: 0.1224
Rougel: 0.2319
Rougelsum: 0.2314
Gen Len: 76.4017
Bert F1: 0.8703

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: 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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len	Bert F1
3.8703	0.6667	20	3.4203	0.3378	0.1167	0.2214	0.2212	57.735	0.8692
3.5213	1.3333	40	3.1803	0.35	0.1227	0.2305	0.2297	65.5641	0.8704
3.389	2.0	60	3.0624	0.3577	0.1269	0.2295	0.2287	70.7949	0.8696
3.2528	2.6667	80	2.9966	0.3707	0.1327	0.2402	0.2393	74.8034	0.8707
3.2518	3.3333	100	2.9522	0.3644	0.1239	0.2318	0.2315	78.1368	0.869
3.1403	4.0	120	2.9272	0.3675	0.1246	0.2325	0.2326	77.1538	0.8701
3.1359	4.6667	140	2.9114	0.3702	0.1294	0.2335	0.2331	78.7692	0.8703
3.1541	5.3333	160	2.8971	0.3701	0.1276	0.2341	0.2341	79.3846	0.8702
3.1552	6.0	180	2.8869	0.3686	0.1254	0.2328	0.2325	79.3932	0.8703
3.1116	6.6667	200	2.8805	0.3618	0.1243	0.2326	0.2319	77.188	0.8697
3.0692	7.3333	220	2.8766	0.3646	0.1259	0.2337	0.2331	77.5556	0.8704
2.9932	8.0	240	2.8726	0.3633	0.1244	0.234	0.2336	76.812	0.8703
3.067	8.6667	260	2.8708	0.3608	0.1234	0.2323	0.2319	76.0769	0.8702
3.0864	9.3333	280	2.8693	0.3608	0.1224	0.2319	0.2314	76.4017	0.8703

Framework versions

Transformers 4.46.3
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.20.3

Library: transformers
Type: t5
License: apache-2.0
Created: Dec 4, 2024
Updated: Dec 4, 2024