t5-3b_rte_sp0_ar0 – AI Model by thrunlab | AlphaNeural AI

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thrunlab/
t5-3b_rte_sp0_ar0

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text-classification

generated_from_trainer

google-t5/t5-3b

autotrain_compatible

text-generation-inference

endpoints_compatible

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t5-3b_rte_sp0_ar0

This model is a fine-tuned version of t5-3b on the glue dataset. It achieves the following results on the evaluation set:

Loss: 3.4268
Accuracy: 0.8876

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: 8
seed: 1
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 20
training_steps: 750

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7306	0.18	25	0.6913	0.5921
0.6717	0.36	50	0.4976	0.8339
0.3978	0.53	75	0.5226	0.8628
0.322	0.71	100	0.3902	0.8484
0.2958	0.89	125	0.3803	0.8881
0.2604	1.07	150	0.8628	0.8736
0.2011	1.25	175	0.7780	0.8953
0.263	1.42	200	2.1533	0.8881
0.2032	1.6	225	4.7955	0.8917
0.2536	1.78	250	1.7810	0.8989
0.1984	1.96	275	0.5119	0.8845
0.1495	2.14	300	0.5128	0.8845
0.1275	2.31	325	0.8602	0.8628
0.0955	2.49	350	1.3642	0.8773
0.3912	2.67	375	1.0186	0.8664
0.1108	2.85	400	2.1450	0.8592
0.0726	3.02	425	2.6801	0.8809
0.0937	3.2	450	5.2053	0.8736
1.0143	3.38	475	3.3979	0.8845
0.5754	3.56	500	4.2786	0.8989
0.2928	3.74	525	5.6543	0.8917
0.5633	3.91	550	6.7064	0.8845
1.0431	4.09	575	4.9205	0.8953
0.2839	4.27	600	4.2344	0.8809
0.5464	4.45	625	4.9598	0.8809
0.0031	4.63	650	5.3705	0.8881
0.5149	4.8	675	4.8105	0.8845
0.2702	4.98	700	6.9958	0.8953
0.7503	5.16	725	5.4360	0.8881
0.2639	5.34	750	5.4420	0.8917

Framework versions

Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0