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---
license: mit
tags:
- generated_from_keras_callback
base_model: cmarkea/distilcamembert-base
model-index:
- name: huynhdoo/distilcamembert-base-finetuned-jva-missions-report
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. -->
# huynhdoo/distilcamembert-base-finetuned-jva-missions-report
This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0336
- Validation Loss: 1.1880
- Train F1: 0.0391
- Epoch: 17
## 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train F1 | Epoch |
|:----------:|:---------------:|:--------:|:-----:|
| 0.5225 | 0.4756 | 0.3575 | 0 |
| 0.4079 | 0.4294 | 0.2961 | 1 |
| 0.3439 | 0.5053 | 0.2961 | 2 |
| 0.2765 | 0.5106 | 0.2346 | 3 |
| 0.2044 | 0.5352 | 0.1788 | 4 |
| 0.1774 | 0.6706 | 0.1341 | 5 |
| 0.1690 | 0.8693 | 0.1676 | 6 |
| 0.1143 | 0.7711 | 0.0726 | 7 |
| 0.0930 | 0.9906 | 0.0950 | 8 |
| 0.1091 | 0.9093 | 0.1117 | 9 |
| 0.0576 | 0.8518 | 0.0894 | 10 |
| 0.0500 | 1.2538 | 0.0950 | 11 |
| 0.0541 | 0.7193 | 0.0838 | 12 |
| 0.0461 | 0.9906 | 0.0503 | 13 |
| 0.0359 | 0.9036 | 0.0447 | 14 |
| 0.0320 | 1.1648 | 0.0391 | 15 |
| 0.0299 | 1.0017 | 0.0279 | 16 |
| 0.0336 | 1.1880 | 0.0391 | 17 |
### Framework versions
- Transformers 4.26.0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2
|