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JamesLemo/
xlm-roberta-self-supervision-classifier

Name: xlm-roberta-self-supervision-classifier
Availability: InStock

generated_from_trainer

JamesLemo/xlm-roberta-self-supervision

finetune

mit

text-embeddings-inference

endpoints_compatible

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xlm-roberta-self-supervision-classifier

This model is a fine-tuned version of JamesLemo/xlm-roberta-self-supervision on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3068

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: 16
eval_batch_size: 8
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: 5

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	50	1.4450
No log	2.0	100	0.9687
No log	3.0	150	0.4570
No log	4.0	200	0.3315
No log	5.0	250	0.3068

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

JamesLemo/xlm-roberta-self-supervision-classifier

xlm-roberta-self-supervision-classifier

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

JamesLemo/
xlm-roberta-self-supervision-classifier