Skip to page content
SAVRN
Search Plan a project

Independent publisher

Clara Wan Ching Ho

c-ho

Models in Library3
Datasets in Library0
Models on Hugging Face75
Followers—

Compare the published evidence

This profile connects the 3 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Token classification.

Reported licenses: mit. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

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: The following hyperparameters were used during training: - learningrate: 5e-05 - trainbatchsize: 8 - evalbatchsize: 8 - gradientaccumulationsteps: 8 - totaltrainbatchsize: 64 - lrschedulertype: linear - lrschedulerwarmupratio: 0.1 - numepochs: 10 - mixedprecisiontraining: Native AMP - Transformers 4.57.6 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.22.2

Open weights mit 559M parameters 514 tokens transformers
View model

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: The following hyperparameters were used during training: - learningrate: 5e-05 - trainbatchsize: 8 - evalbatchsize: 8 - gradientaccumulationsteps: 8 - totaltrainbatchsize: 64 - lrschedulertype: linear - lrschedulerwarmupratio: 0.1 - numepochs: 10 - mixedprecisiontraining: Native AMP - Transformers 4.57.6 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.22.2

Open weights mit 559M parameters 514 tokens transformers
View model

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: The following hyperparameters were used during training: - learningrate: 3e-05 - trainbatchsize: 8 - evalbatchsize: 8 - gradientaccumulationsteps: 8 - totaltrainbatchsize: 64 - lrschedulertype: linear - lrschedulerwarmupratio: 0.1 - numepochs: 10 - mixedprecisiontraining: Native AMP - Transformers 4.57.6 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.22.2

Open weights mit 559M parameters 514 tokens transformers
View model