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---
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
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