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EshAhm/
xlm-roberta-largeFullTune

Name: xlm-roberta-largeFullTune
Availability: InStock

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xlm-roberta-largeFullTune

This model is a fine-tuned version of xlm-roberta-large on SIRIS-Lab/citation-parser-ENTITY dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.1963	1.0	68	0.1978	0.7166	0.8617	0.7825	0.9549
0.1574	2.0	136	0.1378	0.8734	0.9363	0.9038	0.9751
0.0544	3.0	204	0.1184	0.9561	0.9666	0.9613	0.9815
0.0442	4.0	272	0.1188	0.9654	0.9691	0.9673	0.9819
0.0331	5.0	340	0.1121	0.9666	0.9691	0.9679	0.9822
0.0208	6.0	408	0.1237	0.9711	0.9736	0.9724	0.9811
0.0214	7.0	476	0.1213	0.9680	0.9730	0.9705	0.9825
0.0172	8.0	544	0.1295	0.9730	0.9736	0.9733	0.9830
0.0097	9.0	612	0.1236	0.9723	0.9717	0.9720	0.9833
0.0117	10.0	680	0.1300	0.9717	0.9730	0.9724	0.9829