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---
license: apache-2.0
base_model: mpalaval/bert-ner-3
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-4
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-ner-4
This model is a fine-tuned version of [mpalaval/bert-ner-3](https://huggingface.co/mpalaval/bert-ner-3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6352
- Precision: 0.2024
- Recall: 0.4674
- F1: 0.2825
- Accuracy: 0.8901
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 258 | 0.4728 | 0.1508 | 0.4021 | 0.2193 | 0.8795 |
| 0.0801 | 2.0 | 516 | 0.4265 | 0.1744 | 0.4124 | 0.2451 | 0.8906 |
| 0.0801 | 3.0 | 774 | 0.5207 | 0.1564 | 0.4296 | 0.2294 | 0.8761 |
| 0.0513 | 4.0 | 1032 | 0.4908 | 0.1718 | 0.4021 | 0.2407 | 0.8882 |
| 0.0513 | 5.0 | 1290 | 0.5247 | 0.1967 | 0.4089 | 0.2656 | 0.8988 |
| 0.0263 | 6.0 | 1548 | 0.5547 | 0.1902 | 0.4261 | 0.2630 | 0.8955 |
| 0.0263 | 7.0 | 1806 | 0.6413 | 0.1849 | 0.4639 | 0.2644 | 0.8836 |
| 0.0133 | 8.0 | 2064 | 0.6059 | 0.2035 | 0.4742 | 0.2848 | 0.8900 |
| 0.0133 | 9.0 | 2322 | 0.6311 | 0.2041 | 0.4742 | 0.2854 | 0.8906 |
| 0.0088 | 10.0 | 2580 | 0.6352 | 0.2024 | 0.4674 | 0.2825 | 0.8901 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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