metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tapt_seq_bn_amazon_helpfulness_classification_model_v2
results: []
tapt_seq_bn_amazon_helpfulness_classification_model_v2
This model is a fine-tuned version of 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