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---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: kasrahabib/roberta-base-finetuned-iso29148-km_propogated_nf_subs_promise_specific_label_req
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. -->
# kasrahabib/roberta-base-finetuned-iso29148-km_propogated_nf_subs_promise_specific_label_req
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0103
- Validation Loss: 0.0804
- Epoch: 14
## 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': 1155, '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 | Epoch |
|:----------:|:---------------:|:-----:|
| 1.3681 | 0.4433 | 0 |
| 0.3195 | 0.2030 | 1 |
| 0.1566 | 0.1204 | 2 |
| 0.0603 | 0.1235 | 3 |
| 0.0378 | 0.1922 | 4 |
| 0.0707 | 0.1259 | 5 |
| 0.0415 | 0.0797 | 6 |
| 0.0262 | 0.1017 | 7 |
| 0.0228 | 0.0930 | 8 |
| 0.0133 | 0.0820 | 9 |
| 0.0124 | 0.0820 | 10 |
| 0.0113 | 0.0802 | 11 |
| 0.0108 | 0.0802 | 12 |
| 0.0105 | 0.0801 | 13 |
| 0.0103 | 0.0804 | 14 |
### Framework versions
- Transformers 4.40.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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