Edit model card

xlm-roberta-base-wikineural

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

  • Loss: 0.0467

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 128
  • seed: 37912547
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 100000

Training results

Training Loss Epoch Step Validation Loss
0.0858 0.14 10000 0.0817
0.0719 0.28 20000 0.0660
0.0656 0.43 30000 0.0631
0.0598 0.57 40000 0.0574
0.0551 0.71 50000 0.0534
0.0523 0.85 60000 0.0512
0.0519 0.99 70000 0.0484
0.0418 1.13 80000 0.0480
0.042 1.28 90000 0.0469
0.041 1.42 100000 0.0467

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month
19
Safetensors
Model size
277M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for arnabdhar/xlm-roberta-base-wikineural

Quantized
(2)
this model

Datasets used to train arnabdhar/xlm-roberta-base-wikineural