---
base_model: bert-base-uncased
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-amazon-reviews-sentiment-analysis
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-amazon-reviews-sentiment-analysis

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2344
- Accuracy: 0.9198
- F1: 0.9215
- Precision: 0.9263
- Recall: 0.9167

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6741        | 1.0   | 47   | 0.6232          | 0.7594   | 0.7097 | 0.9322    | 0.5729 |
| 0.4346        | 2.0   | 94   | 0.3871          | 0.8717   | 0.875  | 0.875     | 0.875  |
| 0.3593        | 3.0   | 141  | 0.2344          | 0.9198   | 0.9215 | 0.9263    | 0.9167 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1