---
tags:
- generated_from_trainer
model-index:
- name: span-marker-bert-base-multilingual-uncased-multinerd
  results: []
---

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# span-marker-bert-base-multilingual-uncased-multinerd

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0054
- Overall Precision: 0.9275
- Overall Recall: 0.9147
- Overall F1: 0.9210
- Overall Accuracy: 0.9842

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.0157        | 1.0   | 50369  | 0.0048          | 0.9143            | 0.8986         | 0.9064     | 0.9807           |
| 0.003         | 2.0   | 100738 | 0.0047          | 0.9237            | 0.9126         | 0.9181     | 0.9835           |
| 0.0017        | 3.0   | 151107 | 0.0054          | 0.9275            | 0.9147         | 0.9210     | 0.9842           |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3