t5-base-gec-new_data

Luffyt/t5-base-gec-new_data

t5-base-gec-new_data is a machine learning model from Luffyt. 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: Dec 3, 2022
Updated: Dec 3, 2022
SHA: b2f91c09

Model card

From the Hugging Face model README

t5-base-gec-new_data

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

Loss: 0.2636
Rouge1: 80.9191
Rouge2: 72.1033
Rougel: 80.7135
Rougelsum: 80.702
Gen Len: 17.1547

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: 1e-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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.9218	0.2	50	0.6153	57.6131	46.0349	57.1409	57.2367	17.6527
0.6706	0.4	100	0.5047	71.4161	58.032	71.0641	71.0333	17.3962
0.5469	0.6	150	0.4484	74.5881	61.5423	74.311	74.2835	17.3643
0.4922	0.8	200	0.4105	76.2609	63.8102	76.0237	75.9821	17.3253
0.4641	1.0	250	0.3812	77.1152	65.3254	76.8848	76.8505	17.2954
0.4303	1.2	300	0.3585	78.0321	66.8786	77.8416	77.8145	17.2455
0.4088	1.39	350	0.3431	78.4136	67.5929	78.2166	78.1909	17.2325
0.3817	1.59	400	0.3299	78.8418	68.3354	78.6253	78.6123	17.2226
0.3898	1.79	450	0.3183	79.1565	68.9491	78.9458	78.9413	17.2246
0.3729	1.99	500	0.3098	79.4178	69.4412	79.1888	79.1712	17.2166
0.364	2.19	550	0.3008	79.6774	69.8938	79.4064	79.3861	17.1936
0.3411	2.39	600	0.2960	79.8587	70.2089	79.6081	79.592	17.2006
0.3134	2.59	650	0.2901	80.0283	70.589	79.7871	79.7862	17.1906
0.3449	2.79	700	0.2856	80.1987	70.8695	79.9722	79.9612	17.1856
0.3298	2.99	750	0.2801	80.3158	71.1125	80.0688	80.0581	17.1647
0.3235	3.19	800	0.2769	80.4603	71.3189	80.2226	80.1989	17.1557
0.3138	3.39	850	0.2749	80.4406	71.302	80.2032	80.1828	17.1587
0.3152	3.59	900	0.2716	80.5545	71.5128	80.3174	80.2989	17.1577
0.309	3.78	950	0.2692	80.5711	71.5881	80.3434	80.321	17.1577
0.3029	3.98	1000	0.2672	80.6339	71.691	80.4081	80.3889	17.1607
0.3012	4.18	1050	0.2662	80.8062	71.9093	80.5751	80.5748	17.1517
0.3034	4.38	1100	0.2655	80.8201	71.9581	80.5943	80.5971	17.1517
0.2972	4.58	1150	0.2644	80.8875	72.0671	80.6642	80.6618	17.1517
0.2978	4.78	1200	0.2638	80.9266	72.0925	80.7175	80.7107	17.1537
0.3052	4.98	1250	0.2636	80.9191	72.1033	80.7135	80.702	17.1547

Framework versions

Transformers 4.25.1
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

Library: transformers
Type: t5
License: apache-2.0
Created: Dec 3, 2022
Updated: Dec 3, 2022