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NER
0f7f815 verified
---
library_name: transformers
license: apache-2.0
base_model: dslim/distilbert-NER
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-NER-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-NER-finetuned-ner
This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0111
- Precision: 0.8892
- Recall: 0.9189
- F1: 0.9038
- Accuracy: 0.9968
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 270 | 0.0155 | 0.8292 | 0.8918 | 0.8594 | 0.9952 |
| 0.0286 | 2.0 | 540 | 0.0121 | 0.8695 | 0.9198 | 0.8939 | 0.9965 |
| 0.0286 | 3.0 | 810 | 0.0111 | 0.8892 | 0.9189 | 0.9038 | 0.9968 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1