README.md

---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- rotten_tomatoes_movie_review
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-rotten-tomatoes-epochs-2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: rotten_tomatoes_movie_review
      type: rotten_tomatoes_movie_review
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9671669793621013
    - name: F1
      type: f1
      value: 0.9671667193207707
---

<!-- 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. -->

# bert-base-cased-finetuned-rotten-tomatoes-epochs-2

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the rotten_tomatoes_movie_review dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1393
- Accuracy: 0.9672
- F1: 0.9672

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3186        | 1.0   | 34   | 0.1948          | 0.9484   | 0.9484 |
| 0.1837        | 2.0   | 68   | 0.1393          | 0.9672   | 0.9672 |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.0