metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results: []
distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2988
- Precision: 0.8066
- Recall: 0.7644
- F1: 0.7849
- Accuracy: 0.9432
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: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 13 | 1.7619 | 0.0 | 0.0 | 0.0 | 0.6185 |
No log | 2.0 | 26 | 1.4482 | 0.0526 | 0.0052 | 0.0095 | 0.6985 |
No log | 3.0 | 39 | 1.0747 | 0.0417 | 0.0105 | 0.0167 | 0.7429 |
No log | 4.0 | 52 | 0.8462 | 0.2262 | 0.0995 | 0.1382 | 0.7821 |
No log | 5.0 | 65 | 0.6852 | 0.3290 | 0.2670 | 0.2948 | 0.8172 |
No log | 6.0 | 78 | 0.5970 | 0.4346 | 0.4869 | 0.4593 | 0.8684 |
No log | 7.0 | 91 | 0.5108 | 0.5072 | 0.5497 | 0.5276 | 0.8880 |
No log | 8.0 | 104 | 0.4515 | 0.5882 | 0.6283 | 0.6076 | 0.9086 |
No log | 9.0 | 117 | 0.4105 | 0.6305 | 0.6702 | 0.6497 | 0.9169 |
No log | 10.0 | 130 | 0.3755 | 0.7120 | 0.6859 | 0.6987 | 0.9293 |
No log | 11.0 | 143 | 0.3661 | 0.7243 | 0.7016 | 0.7128 | 0.9293 |
No log | 12.0 | 156 | 0.3460 | 0.7273 | 0.7120 | 0.7196 | 0.9313 |
No log | 13.0 | 169 | 0.3287 | 0.7609 | 0.7330 | 0.7467 | 0.9355 |
No log | 14.0 | 182 | 0.3177 | 0.7701 | 0.7539 | 0.7619 | 0.9370 |
No log | 15.0 | 195 | 0.3133 | 0.7705 | 0.7382 | 0.7540 | 0.9360 |
No log | 16.0 | 208 | 0.3028 | 0.7826 | 0.7539 | 0.7680 | 0.9406 |
No log | 17.0 | 221 | 0.3062 | 0.7944 | 0.7487 | 0.7709 | 0.9391 |
No log | 18.0 | 234 | 0.3015 | 0.8011 | 0.7592 | 0.7796 | 0.9411 |
No log | 19.0 | 247 | 0.2997 | 0.7935 | 0.7644 | 0.7787 | 0.9432 |
No log | 20.0 | 260 | 0.2988 | 0.8066 | 0.7644 | 0.7849 | 0.9432 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cpu
- Datasets 2.19.1
- Tokenizers 0.19.1