---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: Self-consciousness_continuous
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Self-consciousness_continuous

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0411
- Rmse: 0.2028
- Mae: 0.1628
- Corr: 0.3046

## 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:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   | Mae    | Corr   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| No log        | 1.0   | 268  | 0.0422          | 0.2055 | 0.1657 | 0.2674 |
| 0.0486        | 2.0   | 536  | 0.0409          | 0.2023 | 0.1637 | 0.2972 |
| 0.0486        | 3.0   | 804  | 0.0411          | 0.2028 | 0.1628 | 0.3046 |


### Framework versions

- Transformers 4.44.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.19.1