---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: miltilingual_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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# miltilingual_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: 1.1201
- Accuracy: 0.6505
- F1 Macro: 0.5674
- Precision Macro: 0.5715
- Recall Macro: 0.5690

## 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: 1e-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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 2.7395        | 1.0    | 1233  | 1.6602          | 0.5501   | 0.3447   | 0.3829          | 0.3645       |
| 1.5662        | 2.0    | 2466  | 1.2526          | 0.6228   | 0.5112   | 0.5447          | 0.5114       |
| 1.2526        | 3.0    | 3699  | 1.1599          | 0.6396   | 0.5478   | 0.5537          | 0.5551       |
| 1.1111        | 4.0    | 4932  | 1.1279          | 0.6469   | 0.5645   | 0.5619          | 0.5745       |
| 0.9426        | 5.0    | 6165  | 1.1201          | 0.6505   | 0.5674   | 0.5715          | 0.5690       |
| 0.8696        | 6.0    | 7398  | 1.1415          | 0.6462   | 0.5620   | 0.5645          | 0.5647       |
| 0.8271        | 7.0    | 8631  | 1.1486          | 0.6467   | 0.5657   | 0.5670          | 0.5667       |
| 0.7772        | 8.0    | 9864  | 1.1642          | 0.6477   | 0.5670   | 0.5644          | 0.5723       |
| 0.7247        | 9.0    | 11097 | 1.1731          | 0.6456   | 0.5644   | 0.5633          | 0.5676       |
| 0.7072        | 9.9922 | 12320 | 1.1731          | 0.6463   | 0.5658   | 0.5657          | 0.5677       |


### Framework versions

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