---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: rating-classifier
  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. -->

# rating-classifier

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:
- F1: 0.6729
- Loss: 0.8373
- Accuracy: 0.6710
- Precision: 0.6774
- Recall: 0.6710

## 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: 16
- eval_batch_size: 16
- 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: 5

### Training results

| Training Loss | Epoch | Step | F1     | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:------:|:---------------:|:--------:|:---------:|:------:|
| 1.0326        | 1.0   | 984  | 0.6354 | 0.8096          | 0.6707   | 0.6383    | 0.6707 |
| 0.6801        | 2.0   | 1968 | 0.6668 | 0.7508          | 0.6888   | 0.6667    | 0.6888 |
| 0.5313        | 3.0   | 2952 | 0.6729 | 0.8373          | 0.6710   | 0.6774    | 0.6710 |
| 0.3895        | 4.0   | 3936 | 0.6678 | 0.9705          | 0.6730   | 0.6649    | 0.6730 |
| 0.2857        | 5.0   | 4920 | 0.6708 | 1.0989          | 0.6745   | 0.6684    | 0.6745 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1