Finetune_XLM_R_large_QA – AI Model by DatTran0509 | AlphaNeural AI

You can deploy this model and start earning money today!

DatTran0509/
Finetune_XLM_R_large_QA

like

0

question-answering

generated_from_trainer

FacebookAI/xlm-roberta-large

endpoints_compatible

Views

No views yet

Finetune_XLM_R_large_QA

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.4169
Exact: 72.8107
F1: 84.3095
Total: 3814
Hasans Exact: 72.8107
Hasans F1: 84.3095
Hasans Total: 3814
Best Exact: 72.8107
Best Exact Thresh: 0.0
Best F1: 84.3095
Best F1 Thresh: 0.0

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: 2e-05
train_batch_size: 10
eval_batch_size: 10
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 20
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Exact	F1	Total	Hasans Exact	Hasans F1	Hasans Total	Best Exact	Best Exact Thresh	Best F1	Best F1 Thresh
1.1561	1.0	1364	1.1712	72.0241	82.5916	3814	72.0241	82.5916	3814	72.0241	0.0	82.5916	0.0
0.8571	2.0	2728	1.2553	75.0131	86.3057	3814	75.0131	86.3057	3814	75.0131	0.0	86.3057	0.0
0.6433	3.0	4092	1.3509	71.4473	82.3763	3814	71.4473	82.3763	3814	71.4473	0.0	82.3763	0.0
0.4305	4.0	5456	1.4169	72.8107	84.3095	3814	72.8107	84.3095	3814	72.8107	0.0	84.3095	0.0

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1