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license: mit
tags:
- generated_from_keras_callback
model-index:
- name: Regression_roberta_1
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. -->
# Regression_roberta_1
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3891
- Train Mae: 0.3117
- Train Mse: 0.1477
- Train R2-score: 0.7113
- Train Accuracy: 0.7077
- Validation Loss: 0.3272
- Validation Mae: 0.3256
- Validation Mse: 0.1253
- Validation R2-score: 0.8839
- Validation Accuracy: 0.9459
- Epoch: 9
## 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': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Mae | Train Mse | Train R2-score | Train Accuracy | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Validation Accuracy | Epoch |
|:----------:|:---------:|:---------:|:--------------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-------------------:|:-----:|
| 0.4486 | 0.2939 | 0.1319 | 0.7250 | 0.7769 | 0.4177 | 0.4165 | 0.2221 | 0.8321 | 0.3243 | 0 |
| 0.3684 | 0.2898 | 0.1342 | 0.5541 | 0.7462 | 0.4019 | 0.4006 | 0.2091 | 0.8409 | 0.3243 | 1 |
| 0.3423 | 0.2854 | 0.1299 | 0.7355 | 0.7462 | 0.3971 | 0.3958 | 0.2050 | 0.8438 | 0.3243 | 2 |
| 0.3514 | 0.2890 | 0.1324 | 0.7935 | 0.7538 | 0.3552 | 0.3538 | 0.1640 | 0.8681 | 0.9459 | 3 |
| 0.3722 | 0.3107 | 0.1525 | 0.5604 | 0.7000 | 0.3448 | 0.3432 | 0.1484 | 0.8750 | 0.9459 | 4 |
| 0.3996 | 0.2949 | 0.1305 | 0.7869 | 0.8231 | 0.3692 | 0.3677 | 0.1794 | 0.8514 | 0.4865 | 5 |
| 0.3441 | 0.2895 | 0.1322 | 0.7546 | 0.7538 | 0.3186 | 0.3169 | 0.1159 | 0.8860 | 0.9459 | 6 |
| 0.3898 | 0.2921 | 0.1255 | 0.5919 | 0.7692 | 0.4107 | 0.4095 | 0.2160 | 0.8366 | 0.3243 | 7 |
| 0.3552 | 0.2868 | 0.1297 | 0.7113 | 0.7538 | 0.4426 | 0.4415 | 0.2434 | 0.8179 | 0.3243 | 8 |
| 0.3891 | 0.3117 | 0.1477 | 0.7113 | 0.7077 | 0.3272 | 0.3256 | 0.1253 | 0.8839 | 0.9459 | 9 |
### Framework versions
- Transformers 4.27.2
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2
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