cs_mT5_0.01_50_v0.2

kmok1/cs_mT5_0.01_50_v0.2

cs_mT5_0.01_50_v0.2 is a machine learning model from kmok1. 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: mt5
Access: Public
Created: Feb 15, 2024
Updated: Feb 15, 2024
SHA: 3c5fada9

Base models

google/mt5-base

Model card

From the Hugging Face model README

cs_mT5_0.01_50_v0.2

This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 6.5103
Bleu: 0.6102
Gen Len: 19.0

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: 0.01
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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
7.711	1.0	6	12.1049	0.1934	17.0952
9.9285	2.0	12	7.2425	0.1897	19.0
6.1686	3.0	18	6.5311	0.3794	19.0
6.0527	4.0	24	6.4394	0.6102	19.0
6.0341	5.0	30	6.3821	0.6102	19.0
4.9353	6.0	36	6.2037	0.704	19.0
5.3025	7.0	42	6.2245	0.2318	19.0
5.4882	8.0	48	6.4244	0.0	19.0
4.3601	9.0	54	6.4695	0.0	19.0
4.8256	10.0	60	6.1939	0.6102	19.0
6.2603	11.0	66	7.2294	0.6102	19.0
5.5046	12.0	72	7.1054	0.704	19.0
5.6536	13.0	78	6.2424	0.6102	19.0
5.2092	14.0	84	6.2343	0.2016	19.0
4.5288	15.0	90	6.1996	0.6102	19.0
5.3447	16.0	96	6.4456	0.0	3.0
4.7282	17.0	102	6.0271	0.2172	19.0
5.3814	18.0	108	6.2591	0.6102	19.0
3.8156	19.0	114	6.2314	0.6102	19.0
4.9031	20.0	120	6.3173	0.1986	19.0
4.4266	21.0	126	6.5376	0.6102	19.0
4.1837	22.0	132	6.1329	0.6405	19.0
4.2994	23.0	138	6.1589	0.6102	19.0
4.3625	24.0	144	6.0873	0.6218	19.0
4.8956	25.0	150	6.2374	0.2318	19.0
4.3551	26.0	156	6.2230	0.6102	19.0
4.025	27.0	162	6.2925	0.6929	19.0
3.9071	28.0	168	6.2040	0.6102	19.0
4.1388	29.0	174	6.3024	0.6218	19.0
3.942	30.0	180	6.4055	0.2176	19.0
4.0977	31.0	186	6.3005	0.2874	19.0
4.6125	32.0	192	6.2886	0.6102	19.0
4.4031	33.0	198	6.2948	0.704	19.0
3.8115	34.0	204	6.2838	0.6102	19.0
4.8767	35.0	210	6.2233	0.6102	19.0
3.6557	36.0	216	6.2860	0.6102	19.0
3.9009	37.0	222	6.3841	0.6102	19.0
4.4334	38.0	228	6.3916	0.6102	19.0
3.3359	39.0	234	6.3696	0.6102	19.0
4.2239	40.0	240	6.4627	0.6102	19.0
3.7335	41.0	246	6.5189	0.6102	19.0
3.544	42.0	252	6.4958	0.6102	19.0
3.77	43.0	258	6.5922	0.6102	19.0
3.4661	44.0	264	6.6700	0.6218	19.0
4.0715	45.0	270	6.6247	0.6102	19.0
3.8948	46.0	276	6.5279	0.6102	19.0
3.8278	47.0	282	6.4594	0.6102	19.0
4.1446	48.0	288	6.4570	0.6102	19.0
3.7627	49.0	294	6.4923	0.6102	19.0
3.5996	50.0	300	6.5103	0.6102	19.0

Framework versions

Transformers 4.35.2
Pytorch 1.13.1+cu117
Datasets 2.17.0
Tokenizers 0.15.1

Library: transformers
Type: mt5
License: apache-2.0
Created: Feb 15, 2024
Updated: Feb 15, 2024