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_mapping
results: []
my_awesome_wnut_model_mapping
This model is a fine-tuned version of distilbert/distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0832
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9821
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: 0.0002
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 118 | 0.0767 | 0.0 | 0.0 | 0.0 | 0.9725 |
| No log | 2.0 | 236 | 0.0554 | 0.0 | 0.0 | 0.0 | 0.9799 |
| No log | 3.0 | 354 | 0.0695 | 0.0 | 0.0 | 0.0 | 0.9799 |
| No log | 4.0 | 472 | 0.0762 | 0.0 | 0.0 | 0.0 | 0.9795 |
| 0.0497 | 5.0 | 590 | 0.0888 | 0.0 | 0.0 | 0.0 | 0.9804 |
| 0.0497 | 6.0 | 708 | 0.0820 | 0.0 | 0.0 | 0.0 | 0.9812 |
| 0.0497 | 7.0 | 826 | 0.0877 | 0.0 | 0.0 | 0.0 | 0.9814 |
| 0.0497 | 8.0 | 944 | 0.0864 | 0.0 | 0.0 | 0.0 | 0.9815 |
| 0.003 | 9.0 | 1062 | 0.0876 | 0.0 | 0.0 | 0.0 | 0.9823 |
| 0.003 | 10.0 | 1180 | 0.0832 | 0.0 | 0.0 | 0.0 | 0.9821 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1
- Datasets 2.19.0
- Tokenizers 0.19.1