---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tapt_seq_bn_amazon_helpfulness_classification_model_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. -->

# tapt_seq_bn_amazon_helpfulness_classification_model_v2

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: 0.3540
- Accuracy: 0.864
- F1 Macro: 0.6950

## 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: 0.0001
- 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
| 0.3384        | 1.0   | 1563  | 0.3308          | 0.8586   | 0.6739   |
| 0.3245        | 2.0   | 3126  | 0.3256          | 0.8652   | 0.6719   |
| 0.3258        | 3.0   | 4689  | 0.3408          | 0.8674   | 0.6464   |
| 0.3309        | 4.0   | 6252  | 0.3150          | 0.8678   | 0.6527   |
| 0.292         | 5.0   | 7815  | 0.3226          | 0.8692   | 0.6787   |
| 0.2756        | 6.0   | 9378  | 0.3384          | 0.8688   | 0.6498   |
| 0.2584        | 7.0   | 10941 | 0.3489          | 0.8654   | 0.6946   |
| 0.2758        | 8.0   | 12504 | 0.3540          | 0.864    | 0.6950   |
| 0.2476        | 9.0   | 14067 | 0.3540          | 0.8668   | 0.6688   |
| 0.2303        | 10.0  | 15630 | 0.3686          | 0.8662   | 0.6542   |


### Framework versions

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