---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: minhnb/ssbc_model_spearman
  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. -->

# minhnb/ssbc_model_spearman

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: 0.0819
- Validation Loss: 0.2328
- Train Spearmanr: 0.8350
- 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4960, '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 | Train Spearmanr | Epoch |
|:----------:|:---------------:|:---------------:|:-----:|
| 0.8155     | 0.3068          | 0.7769          | 0     |
| 0.2629     | 0.2419          | 0.8209          | 1     |
| 0.2026     | 0.2604          | 0.8161          | 2     |
| 0.1684     | 0.2323          | 0.8264          | 3     |
| 0.1375     | 0.2442          | 0.8282          | 4     |
| 0.1186     | 0.2473          | 0.8334          | 5     |
| 0.1055     | 0.2452          | 0.8328          | 6     |
| 0.0947     | 0.2258          | 0.8347          | 7     |
| 0.0890     | 0.2347          | 0.8335          | 8     |
| 0.0819     | 0.2328          | 0.8350          | 9     |


### Framework versions

- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1