---
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-base-cased
model-index:
- name: finetuned-Sentiment-classfication-BERT-model
  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. -->

# finetuned-Sentiment-classfication-BERT-model

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6056
- Rmse: 0.6890

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7754        | 2.0   | 500  | 0.6056          | 0.6890 |
| 0.3975        | 4.0   | 1000 | 0.6982          | 0.6452 |
| 0.1308        | 6.0   | 1500 | 1.0715          | 0.6643 |
| 0.0526        | 8.0   | 2000 | 1.3439          | 0.6571 |
| 0.0241        | 10.0  | 2500 | 1.4676          | 0.6695 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3