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license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: letingliu/holder_type2
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. -->
# letingliu/holder_type2
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: 0.4652
- Validation Loss: 0.4554
- Train Accuracy: 0.9333
- Epoch: 19
## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 35, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.6797 | 0.6563 | 0.8583 | 0 |
| 0.6380 | 0.5999 | 0.8833 | 1 |
| 0.5750 | 0.5293 | 0.9 | 2 |
| 0.5168 | 0.4771 | 0.925 | 3 |
| 0.4718 | 0.4554 | 0.9333 | 4 |
| 0.4703 | 0.4554 | 0.9333 | 5 |
| 0.4732 | 0.4554 | 0.9333 | 6 |
| 0.4659 | 0.4554 | 0.9333 | 7 |
| 0.4621 | 0.4554 | 0.9333 | 8 |
| 0.4751 | 0.4554 | 0.9333 | 9 |
| 0.4686 | 0.4554 | 0.9333 | 10 |
| 0.4647 | 0.4554 | 0.9333 | 11 |
| 0.4735 | 0.4554 | 0.9333 | 12 |
| 0.4699 | 0.4554 | 0.9333 | 13 |
| 0.4719 | 0.4554 | 0.9333 | 14 |
| 0.4701 | 0.4554 | 0.9333 | 15 |
| 0.4672 | 0.4554 | 0.9333 | 16 |
| 0.4561 | 0.4554 | 0.9333 | 17 |
| 0.4717 | 0.4554 | 0.9333 | 18 |
| 0.4652 | 0.4554 | 0.9333 | 19 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
|