metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model_2
results: []
my_awesome_wnut_model_2
This model is a fine-tuned version of distilbert/distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0982
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9814
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: 13
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 118 | 0.0915 | 0.0 | 0.0 | 0.0 | 0.9808 |
| No log | 2.0 | 236 | 0.0942 | 0.0 | 0.0 | 0.0 | 0.9812 |
| No log | 3.0 | 354 | 0.1112 | 0.0 | 0.0 | 0.0 | 0.9786 |
| No log | 4.0 | 472 | 0.0931 | 0.0 | 0.0 | 0.0 | 0.9806 |
| 0.0017 | 5.0 | 590 | 0.1000 | 0.0 | 0.0 | 0.0 | 0.9810 |
| 0.0017 | 6.0 | 708 | 0.0925 | 0.0 | 0.0 | 0.0 | 0.9810 |
| 0.0017 | 7.0 | 826 | 0.0976 | 0.0 | 0.0 | 0.0 | 0.9815 |
| 0.0017 | 8.0 | 944 | 0.0930 | 0.0 | 0.0 | 0.0 | 0.9815 |
| 0.0012 | 9.0 | 1062 | 0.1012 | 0.0 | 0.0 | 0.0 | 0.9810 |
| 0.0012 | 10.0 | 1180 | 0.0993 | 0.0 | 0.0 | 0.0 | 0.9814 |
| 0.0012 | 11.0 | 1298 | 0.0995 | 0.0 | 0.0 | 0.0 | 0.9812 |
| 0.0012 | 12.0 | 1416 | 0.0975 | 0.0 | 0.0 | 0.0 | 0.9814 |
| 0.0006 | 13.0 | 1534 | 0.0982 | 0.0 | 0.0 | 0.0 | 0.9814 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0