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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: clapAI/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. -->
# clapAI/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
|