metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-requirements
results: []
bert-finetuned-ner-requirements
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9697
- Precision: 0.2404
- Recall: 0.3788
- F1: 0.2941
- Accuracy: 0.75
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 | 10 | 1.5976 | 0.0 | 0.0 | 0.0 | 0.7226 |
| No log | 2.0 | 20 | 1.2824 | 0.1364 | 0.1364 | 0.1364 | 0.7555 |
| No log | 3.0 | 30 | 1.1017 | 0.1829 | 0.2273 | 0.2027 | 0.7464 |
| No log | 4.0 | 40 | 1.0788 | 0.1321 | 0.2121 | 0.1628 | 0.7464 |
| No log | 5.0 | 50 | 1.0091 | 0.1651 | 0.2727 | 0.2057 | 0.7482 |
| No log | 6.0 | 60 | 0.9949 | 0.1667 | 0.2879 | 0.2111 | 0.7427 |
| No log | 7.0 | 70 | 0.9766 | 0.2 | 0.3182 | 0.2456 | 0.7536 |
| No log | 8.0 | 80 | 0.9734 | 0.2202 | 0.3636 | 0.2743 | 0.7482 |
| No log | 9.0 | 90 | 0.9744 | 0.2336 | 0.3788 | 0.2890 | 0.75 |
| No log | 10.0 | 100 | 0.9697 | 0.2404 | 0.3788 | 0.2941 | 0.75 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1