---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: song-coherency-classifier-v2
  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. -->

# song-coherency-classifier-v2

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1341
- F1: [0.9784946236559139, 0.9789473684210526]

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1                                       |
|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------:|
| No log        | 1.0   | 190  | 0.0924          | [0.9760000000000001, 0.9761273209549072] |
| No log        | 2.0   | 380  | 0.0926          | [0.9754768392370572, 0.9766233766233766] |
| 0.1717        | 3.0   | 570  | 0.0825          | [0.9810298102981029, 0.9817232375979111] |
| 0.1717        | 4.0   | 760  | 0.0892          | [0.9813333333333334, 0.9814323607427056] |
| 0.1717        | 5.0   | 950  | 0.0788          | [0.9838709677419355, 0.9842105263157895] |
| 0.0737        | 6.0   | 1140 | 0.1032          | [0.9813333333333334, 0.9814323607427056] |
| 0.0737        | 7.0   | 1330 | 0.1212          | [0.9783783783783783, 0.9790575916230367] |
| 0.0538        | 8.0   | 1520 | 0.1010          | [0.9786096256684492, 0.9788359788359788] |
| 0.0538        | 9.0   | 1710 | 0.1186          | [0.9811320754716981, 0.9816272965879265] |
| 0.0538        | 10.0  | 1900 | 0.1341          | [0.9784946236559139, 0.9789473684210526] |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1