---
library_name: transformers
license: mit
base_model: roberta-large
tags:
- generated_from_keras_callback
model-index:
- name: relationship_classifier_multi_retrained
  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. -->

# relationship_classifier_multi_retrained

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on a dataset from OYM 1:1 vs. 2:1 early literacy online tutoring. 
It achieves the following results on the evaluation set:
- Train Loss: 0.2570
- Validation Loss: 0.3345
- Train Accuracy: 0.8891
- Epoch: 2

## Model description

This model is a retrained version of https://huggingface.co/StanfordSCALE/relationship_classifier_multi that corrects for overfitting in the previous model. 

## Intended uses & limitations

This model was trained on online literacy tutoring data for grades K-2. Generalization beyond this context is uncertain. 

## 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': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 454, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 50, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.8833     | 0.6258          | 0.7781         | 0     |
| 0.4531     | 0.3678          | 0.8713         | 1     |
| 0.2570     | 0.3345          | 0.8891         | 2     |


### Framework versions

- Transformers 4.51.3
- TensorFlow 2.19.0
- Datasets 4.8.5
- Tokenizers 0.21.4