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

# roberta_base_amazon

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: 0.6847
- Accuracy: 0.8057
- F1 Macro: 0.7452
- F1 Micro: 0.8057

## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.0556        | 0.26  | 50   | 1.7788          | 0.6166   | 0.4632   | 0.6166   |
| 1.2395        | 0.53  | 100  | 1.1504          | 0.7141   | 0.6033   | 0.7141   |
| 0.9724        | 0.79  | 150  | 0.9645          | 0.7385   | 0.6450   | 0.7385   |
| 0.8878        | 1.05  | 200  | 0.8704          | 0.7734   | 0.7001   | 0.7734   |
| 0.7261        | 1.32  | 250  | 0.8159          | 0.7767   | 0.7188   | 0.7767   |
| 0.8083        | 1.58  | 300  | 0.7718          | 0.7879   | 0.7241   | 0.7879   |
| 0.7209        | 1.84  | 350  | 0.7307          | 0.7997   | 0.7414   | 0.7997   |
| 0.6535        | 2.11  | 400  | 0.7205          | 0.8043   | 0.7452   | 0.8043   |
| 0.6283        | 2.37  | 450  | 0.7047          | 0.8090   | 0.7498   | 0.8090   |
| 0.5214        | 2.63  | 500  | 0.6879          | 0.8109   | 0.7541   | 0.8109   |
| 0.5808        | 2.89  | 550  | 0.6847          | 0.8057   | 0.7452   | 0.8057   |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2