---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tapt_seq_bn_amazon_helpfulness_classification_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tapt_seq_bn_amazon_helpfulness_classification_model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3322
- Accuracy: 0.866
- F1 Macro: 0.5934

## 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=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.3392        | 1.0   | 1563 | 0.3329          | 0.859    | 0.5394   |
| 0.3347        | 2.0   | 3126 | 0.3382          | 0.863    | 0.5814   |
| 0.3305        | 3.0   | 4689 | 0.3322          | 0.866    | 0.5934   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2