|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: JcKosmos74/my_awesome_wnut_model |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information Keras had access to. You should |
|
probably proofread and complete it, then remove this comment. --> |
|
|
|
# JcKosmos74/my_awesome_wnut_model |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 0.1232 |
|
- Validation Loss: 0.2581 |
|
- Train Precision: 0.5543 |
|
- Train Recall: 0.4091 |
|
- Train F1: 0.4708 |
|
- Train Accuracy: 0.9444 |
|
- Epoch: 2 |
|
|
|
## 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: |
|
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 636, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
|
- training_precision: float32 |
|
|
|
### Training results |
|
|
|
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch | |
|
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
|
| 0.3220 | 0.3166 | 0.3671 | 0.0909 | 0.1457 | 0.9273 | 0 | |
|
| 0.1617 | 0.2656 | 0.5199 | 0.3600 | 0.4254 | 0.9409 | 1 | |
|
| 0.1232 | 0.2581 | 0.5543 | 0.4091 | 0.4708 | 0.9444 | 2 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.2 |
|
- TensorFlow 2.13.0 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
