---
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