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---
tags:
- generated_from_trainer
model-index:
- name: span-marker-bert-base-multilingual-uncased-multinerd
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. -->
# 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
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