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library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: 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. -->
# ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|
| 0.1717 | 1.0 | 125 | 0.0026 | 1.0 | 1.0 | 1.0 |
| 0.0022 | 2.0 | 250 | 0.0007 | 1.0 | 1.0 | 1.0 |
| 0.0014 | 3.0 | 375 | 0.0004 | 1.0 | 1.0 | 1.0 |
| 0.0010 | 4.0 | 500 | 0.0004 | 1.0 | 1.0 | 1.0 |
| 0.0008 | 5.0 | 625 | 0.0003 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 5.8.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2
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