README.md

metadata

library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
  - generated_from_trainer
metrics:
  - f1
  - precision
  - recall
model-index:
  - name: modernBERT-base-multilingual-sentiment
    results: []

modernBERT-base-multilingual-sentiment

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

• Loss: 1.8330
• F1: 0.1291
• Precision: 0.1650
• Recall: 0.1890

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: 6e-05
• train_batch_size: 1024
• eval_batch_size: 1024
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 2048
• total_eval_batch_size: 2048
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.01
• num_epochs: 2.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall
1.8373	1.0	8	1.8330	0.1291	0.1650	0.1890
1.8364	2.0	16	1.8330	0.1291	0.1650	0.1890

Framework versions

• Transformers 4.48.0.dev0
• Pytorch 2.4.0+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0