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license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-base-multilingual-cased-finetuned-ner
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. -->
# bert-base-multilingual-cased-finetuned-ner
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2939
- Accuracy: 0.4501
- Precision: 0.5440
- Recall: 0.6659
- F1: 0.4954
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 50 | 0.5390 | 0.3903 | 0.5183 | 0.4448 | 0.3118 |
| No log | 2.0 | 100 | 0.4150 | 0.4152 | 0.5575 | 0.5062 | 0.3632 |
| No log | 3.0 | 150 | 0.3530 | 0.4289 | 0.5842 | 0.5557 | 0.3945 |
| No log | 4.0 | 200 | 0.3272 | 0.4348 | 0.5319 | 0.5761 | 0.4145 |
| No log | 5.0 | 250 | 0.3047 | 0.4401 | 0.5175 | 0.6018 | 0.4284 |
| No log | 6.0 | 300 | 0.2964 | 0.4422 | 0.5224 | 0.6224 | 0.4600 |
| No log | 7.0 | 350 | 0.2927 | 0.4445 | 0.5391 | 0.6302 | 0.4691 |
| No log | 8.0 | 400 | 0.2896 | 0.4457 | 0.5295 | 0.6335 | 0.4668 |
| No log | 9.0 | 450 | 0.2810 | 0.4482 | 0.5360 | 0.6535 | 0.4846 |
| 0.324 | 10.0 | 500 | 0.2852 | 0.4486 | 0.5383 | 0.6554 | 0.4847 |
| 0.324 | 11.0 | 550 | 0.2949 | 0.4482 | 0.5372 | 0.6560 | 0.4858 |
| 0.324 | 12.0 | 600 | 0.2938 | 0.4494 | 0.5437 | 0.6603 | 0.4917 |
| 0.324 | 13.0 | 650 | 0.2906 | 0.4503 | 0.5437 | 0.6664 | 0.4952 |
| 0.324 | 14.0 | 700 | 0.2963 | 0.4499 | 0.5466 | 0.6641 | 0.4957 |
| 0.324 | 15.0 | 750 | 0.2939 | 0.4501 | 0.5440 | 0.6659 | 0.4954 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|