---
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: 1.1210
- Accuracy: 0.6499
- F1 Macro: 0.5631
- Precision Macro: 0.5636
- Recall Macro: 0.5672

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 2.4454        | 1.0    | 1233 | 1.4217          | 0.5971   | 0.4617   | 0.5194          | 0.4599       |
| 1.3605        | 2.0    | 2466 | 1.1851          | 0.6360   | 0.5358   | 0.5534          | 0.5358       |
| 1.1562        | 3.0    | 3699 | 1.1435          | 0.6424   | 0.5511   | 0.5580          | 0.5552       |
| 1.0514        | 4.0    | 4932 | 1.1216          | 0.6487   | 0.5621   | 0.5628          | 0.5673       |
| 0.9556        | 4.9962 | 6160 | 1.1210          | 0.6499   | 0.5631   | 0.5636          | 0.5672       |


### Framework versions

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