---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: multilingual_dbert_linsearch_only_abstract
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# multilingual_dbert_linsearch_only_abstract

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5452
- Accuracy: 0.6465
- F1 Macro: 0.5744
- Precision Macro: 0.5998
- Recall Macro: 0.5660

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.2
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 1.3208        | 1.0   | 19722 | 1.2841          | 0.6142   | 0.5160   | 0.5368          | 0.5359       |
| 1.1135        | 2.0   | 39444 | 1.1921          | 0.6449   | 0.5597   | 0.5673          | 0.5575       |
| 0.8989        | 3.0   | 59166 | 1.2967          | 0.6495   | 0.5643   | 0.5834          | 0.5573       |
| 0.7155        | 4.0   | 78888 | 1.5452          | 0.6465   | 0.5744   | 0.5998          | 0.5660       |
| 0.5373        | 5.0   | 98610 | 1.7780          | 0.6400   | 0.5669   | 0.5895          | 0.5605       |


### Framework versions

- Transformers 4.50.1
- Pytorch 2.5.1+cu121
- Datasets 3.4.1
- Tokenizers 0.21.1