---
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: []
---

<!-- 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. -->

# modernBERT-base-multilingual-sentiment

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/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