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

# distilbert_base_uncased_amazon

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9130
- Accuracy: 0.7576
- F1 Macro: 0.6904
- F1 Micro: 0.7576

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.6322        | 0.26  | 50   | 2.5191          | 0.4750   | 0.3209   | 0.4750   |
| 1.9044        | 0.53  | 100  | 1.8323          | 0.6014   | 0.4626   | 0.6014   |
| 1.5127        | 0.79  | 150  | 1.4810          | 0.6574   | 0.5154   | 0.6574   |
| 1.2857        | 1.05  | 200  | 1.2679          | 0.6983   | 0.5795   | 0.6983   |
| 1.0669        | 1.32  | 250  | 1.1415          | 0.7306   | 0.6376   | 0.7306   |
| 1.0931        | 1.58  | 300  | 1.0669          | 0.7312   | 0.6333   | 0.7312   |
| 0.9879        | 1.84  | 350  | 1.0102          | 0.7437   | 0.6542   | 0.7437   |
| 0.8936        | 2.11  | 400  | 0.9650          | 0.7444   | 0.6640   | 0.7444   |
| 0.8345        | 2.37  | 450  | 0.9389          | 0.7582   | 0.6900   | 0.7582   |
| 0.7851        | 2.63  | 500  | 0.9208          | 0.7628   | 0.6924   | 0.7628   |
| 0.8439        | 2.89  | 550  | 0.9130          | 0.7576   | 0.6904   | 0.7576   |


### Framework versions

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