---
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta_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. -->

# distilroberta_base_amazon

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7775
- Accuracy: 0.7826
- F1 Macro: 0.7137
- F1 Micro: 0.7826

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.2364        | 0.26  | 50   | 1.9915          | 0.5487   | 0.3934   | 0.5487   |
| 1.4061        | 0.53  | 100  | 1.3136          | 0.6449   | 0.5030   | 0.6449   |
| 1.1502        | 0.79  | 150  | 1.1137          | 0.6937   | 0.5697   | 0.6937   |
| 1.0396        | 1.05  | 200  | 0.9888          | 0.7358   | 0.6345   | 0.7358   |
| 0.86          | 1.32  | 250  | 0.9200          | 0.7437   | 0.6560   | 0.7437   |
| 0.9646        | 1.58  | 300  | 0.8704          | 0.7497   | 0.6626   | 0.7497   |
| 0.8749        | 1.84  | 350  | 0.8367          | 0.7708   | 0.6960   | 0.7708   |
| 0.8031        | 2.11  | 400  | 0.8125          | 0.7767   | 0.7069   | 0.7767   |
| 0.7728        | 2.37  | 450  | 0.7912          | 0.7787   | 0.7085   | 0.7787   |
| 0.7164        | 2.63  | 500  | 0.7829          | 0.7793   | 0.7068   | 0.7793   |
| 0.7533        | 2.89  | 550  | 0.7775          | 0.7826   | 0.7137   | 0.7826   |


### Framework versions

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