---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- poem_sentiment
metrics:
- accuracy
model-index:
- name: Bert_uncased_fine_tuned_Reward_Model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: poem_sentiment
      type: poem_sentiment
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.875
---

<!-- 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. -->

# Bert_uncased_fine_tuned_Reward_Model

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the poem_sentiment dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0876
- Mse: 0.0876
- Mae: 0.1403
- R2: 0.7389
- Accuracy: 0.875

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
| No log        | 1.0   | 53   | 0.1744          | 0.1744 | 0.2973 | 0.4805 | 0.7885   |
| No log        | 2.0   | 106  | 0.1074          | 0.1074 | 0.2333 | 0.6801 | 0.8846   |
| No log        | 3.0   | 159  | 0.1026          | 0.1026 | 0.2134 | 0.6943 | 0.8654   |
| No log        | 4.0   | 212  | 0.0877          | 0.0877 | 0.1841 | 0.7388 | 0.8942   |
| No log        | 5.0   | 265  | 0.1000          | 0.1000 | 0.2007 | 0.7021 | 0.8942   |
| No log        | 6.0   | 318  | 0.0863          | 0.0863 | 0.1738 | 0.7429 | 0.8942   |
| No log        | 7.0   | 371  | 0.0966          | 0.0966 | 0.1827 | 0.7122 | 0.8846   |
| No log        | 8.0   | 424  | 0.0946          | 0.0946 | 0.1701 | 0.7183 | 0.8846   |
| No log        | 9.0   | 477  | 0.0978          | 0.0978 | 0.1658 | 0.7088 | 0.875    |
| 0.0516        | 10.0  | 530  | 0.0854          | 0.0854 | 0.1639 | 0.7457 | 0.875    |
| 0.0516        | 11.0  | 583  | 0.0947          | 0.0947 | 0.1620 | 0.7181 | 0.8846   |
| 0.0516        | 12.0  | 636  | 0.0907          | 0.0907 | 0.1516 | 0.7297 | 0.8846   |
| 0.0516        | 13.0  | 689  | 0.0885          | 0.0885 | 0.1546 | 0.7364 | 0.875    |
| 0.0516        | 14.0  | 742  | 0.0849          | 0.0849 | 0.1452 | 0.7471 | 0.8942   |
| 0.0516        | 15.0  | 795  | 0.0823          | 0.0823 | 0.1428 | 0.7548 | 0.8846   |
| 0.0516        | 16.0  | 848  | 0.0864          | 0.0864 | 0.1429 | 0.7427 | 0.8846   |
| 0.0516        | 17.0  | 901  | 0.0854          | 0.0854 | 0.1427 | 0.7457 | 0.8846   |
| 0.0516        | 18.0  | 954  | 0.0860          | 0.0860 | 0.1429 | 0.7437 | 0.875    |
| 0.0059        | 19.0  | 1007 | 0.0871          | 0.0871 | 0.1438 | 0.7406 | 0.875    |
| 0.0059        | 20.0  | 1060 | 0.0876          | 0.0876 | 0.1403 | 0.7389 | 0.875    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2