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sytnaxerror/
xlm-roberta-large-with-concat-pc

Name: xlm-roberta-large-with-concat-pc
Availability: InStock

generated_from_trainer

DTAI-KULeuven/robbert-2023-dutch-large

finetune

mit

text-embeddings-inference

endpoints_compatible

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xlm-roberta-large-with-dbrb-pc

This model is a fine-tuned version of DTAI-KULeuven/robbert-2023-dutch-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6931
Accuracy: 0.5001

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: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.8079	1.0	2814	0.6934	0.4999
2.7877	2.0	5628	0.6968	0.5001
2.7811	3.0	8442	0.6931	0.5001

Framework versions

Transformers 5.4.0
Pytorch 2.9.1+cu130
Datasets 4.8.4
Tokenizers 0.22.2

sytnaxerror/xlm-roberta-large-with-concat-pc

xlm-roberta-large-with-dbrb-pc

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sytnaxerror/
xlm-roberta-large-with-concat-pc