ER_new_context – AI Model by tringuyen-uit | AlphaNeural AI

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tringuyen-uit/
ER_new_context

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question-answering

generated_from_trainer

VietAI/vit5-base

text-generation-inference

endpoints_compatible

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ER_new_context

This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4057

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
3.2979	0.1	100	1.2437
1.1026	0.19	200	0.7365
0.7482	0.29	300	0.5781
0.6258	0.38	400	0.5159
0.5153	0.48	500	0.4504
0.4802	0.57	600	0.4455
0.4905	0.67	700	0.4059
0.382	0.76	800	0.4778
0.3728	0.86	900	0.3985
0.3274	0.96	1000	0.3982
0.3639	1.05	1100	0.4184
0.2881	1.15	1200	0.4454
0.3194	1.24	1300	0.3778
0.2695	1.34	1400	0.3957
0.2894	1.43	1500	0.4000
0.276	1.53	1600	0.3984
0.2325	1.62	1700	0.3627
0.2192	1.72	1800	0.3782
0.279	1.81	1900	0.4161
0.2636	1.91	2000	0.4026
0.2932	2.01	2100	0.3232
0.206	2.1	2200	0.3633
0.1865	2.2	2300	0.4019
0.1651	2.29	2400	0.4385
0.167	2.39	2500	0.4277
0.1705	2.48	2600	0.4083
0.2321	2.58	2700	0.3667
0.1912	2.67	2800	0.3772
0.192	2.77	2900	0.4032
0.1881	2.87	3000	0.4059
0.152	2.96	3100	0.4057

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2