roberta-base-azerbaijani

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

This model is a continued pre-trained version of xlm-roberta-base on a various cleaned community corpus. It achieves the following results on the evaluation set:

• Loss: 1.1697

We thank Microsoft Accelerating Foundation Models Research Program for supporting our research. Authors: Mammad Hajili, Duygu Ataman

Model description

The model was trained on masked language model task on a single V100 GPU for 68 hours. For downstream tasks, it requires to be fine-tuned based on objective of the task.

Training and evaluation data

The training data is clean mix of various Azerbaijani corpus shared by the community.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0
• mixed_precision_training: Native AMP

Training results

• Validation loss at epoch 3: 1.1697
• Perplexity at epoch 3: 3.22

Framework versions

• Transformers 4.40.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1