---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: finetuned-Sentiment-classfication-DistilBert-model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuned-Sentiment-classfication-DistilBert-model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2764
- Rmse: 0.2925

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7292        | 2.72  | 500  | 0.3805          | 0.5119 |
| 0.1778        | 5.43  | 1000 | 0.2802          | 0.3530 |
| 0.0487        | 8.15  | 1500 | 0.2764          | 0.2925 |
| 0.0209        | 10.86 | 2000 | 0.2921          | 0.2860 |
| 0.0113        | 13.58 | 2500 | 0.3244          | 0.2884 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3