---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Regression_bert_10
  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_bert_10

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: 0.0535
- Train Mae: 0.2673
- Train Mse: 0.1031
- Train R2-score: 0.6896
- Validation Loss: 0.1142
- Validation Mae: 0.3549
- Validation Mse: 0.1957
- Validation R2-score: 0.9230
- 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': 1e-04, '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 | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Epoch |
|:----------:|:---------:|:---------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-----:|
| 0.2988     | 0.4759    | 0.3361    | 0.6079         | 0.1967          | 0.3939         | 0.2542         | 0.9026              | 0     |
| 0.1715     | 0.4010    | 0.2357    | 0.6812         | 0.1680          | 0.4014         | 0.2478         | 0.9049              | 1     |
| 0.0903     | 0.3374    | 0.1532    | 0.8384         | 0.1354          | 0.3432         | 0.1971         | 0.9210              | 2     |
| 0.0636     | 0.3139    | 0.1272    | 0.4117         | 0.1538          | 0.4066         | 0.2304         | 0.9034              | 3     |
| 0.0746     | 0.3142    | 0.1294    | 0.9220         | 0.1184          | 0.3589         | 0.2015         | 0.9224              | 4     |
| 0.0604     | 0.2837    | 0.1119    | 0.9439         | 0.1268          | 0.3450         | 0.1994         | 0.9209              | 5     |
| 0.0556     | 0.2660    | 0.1049    | 0.6002         | 0.1193          | 0.3037         | 0.1704         | 0.9265              | 6     |
| 0.0541     | 0.2581    | 0.1007    | 0.8081         | 0.1125          | 0.3350         | 0.1743         | 0.9229              | 7     |
| 0.0532     | 0.2679    | 0.1044    | 0.8917         | 0.1109          | 0.3131         | 0.1757         | 0.9311              | 8     |
| 0.0535     | 0.2673    | 0.1031    | 0.6896         | 0.1142          | 0.3549         | 0.1957         | 0.9230              | 9     |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.2