results_ara_t5_v2

hiba2/results_ara_t5_v2

results_ara_t5_v2 is a machine learning model from hiba2. 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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Hugging Face

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At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Apr 4, 2024
Updated: Apr 4, 2024
SHA: 21c5e0ba

Base models

bakrianoo/t5-arabic-base

Model card

From the Hugging Face model README

results_ara_t5_v2

This model is a fine-tuned version of bakrianoo/t5-arabic-base on an unknown dataset. It achieves the following results on the evaluation set:

Gen Len: 19.0
Loss: 0.0001
Rouge1: 0.0875
Rouge2: 0.0046
Rougel: 0.0871
Rougelsum: 0.0873

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 10

Training results

Training Loss	Epoch	Step	Gen Len	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
5.4255	0.43	500	18.8641	0.0292	0.0123	0.0028	0.0122	0.0122
0.0975	0.86	1000	18.7006	0.0101	0.0146	0.0038	0.0146	0.0146
0.0321	1.29	1500	18.5583	0.0077	0.078	0.0046	0.0779	0.078
0.0237	1.71	2000	18.7994	0.0075	0.0806	0.0066	0.0809	0.0805
0.0182	2.14	2500	19.0	0.0072	0.0761	0.0023	0.0759	0.076
0.0148	2.57	3000	18.8528	0.0069	0.0952	0.0061	0.0957	0.0951
0.0156	3.0	3500	19.0	0.0064	0.0773	0.0036	0.0772	0.0772
0.0126	3.43	4000	18.5583	0.0060	0.0859	0.0038	0.0862	0.0862
0.0165	3.86	4500	18.8528	0.0056	0.0832	0.0075	0.0835	0.0833
0.0101	4.28	5000	19.0	0.0047	0.0846	0.0052	0.0853	0.0848
0.0089	4.71	5500	19.0	0.0022	0.0874	0.0046	0.0871	0.0873
0.0063	5.14	6000	19.0	0.0009	0.0875	0.0046	0.0871	0.0873
0.0051	5.57	6500	19.0	0.0003	0.0875	0.0046	0.0871	0.0873
0.0042	6.0	7000	19.0	0.0002	0.0875	0.0046	0.0871	0.0873
0.0037	6.43	7500	19.0	0.0002	0.0875	0.0046	0.0871	0.0873
0.0035	6.86	8000	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.003	7.28	8500	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.0027	7.71	9000	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.0024	8.14	9500	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.0023	8.57	10000	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.0022	9.0	10500	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.002	9.43	11000	19.0	0.0001	0.0875	0.0046	0.0871	0.0873
0.0019	9.85	11500	19.0	0.0001	0.0875	0.0046	0.0871	0.0873

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

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