metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-model
results: []
ner-model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2825
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.92
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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 3 | 0.5806 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 2.0 | 6 | 0.3634 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 3.0 | 9 | 0.3389 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 4.0 | 12 | 0.3395 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 5.0 | 15 | 0.3212 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 6.0 | 18 | 0.3025 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 7.0 | 21 | 0.2912 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 8.0 | 24 | 0.2857 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 9.0 | 27 | 0.2832 | 0.0 | 0.0 | 0.0 | 0.92 |
| No log | 10.0 | 30 | 0.2825 | 0.0 | 0.0 | 0.0 | 0.92 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0