---
base_model: finiteautomata/bertweet-base-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: model_IMDB_peft
  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. -->

# model_IMDB_peft

This model is a fine-tuned version of [finiteautomata/bertweet-base-sentiment-analysis](https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2832
- Accuracy: 0.8872

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3355        | 1.0   | 1563  | 0.3167          | 0.8643   |
| 0.3203        | 2.0   | 3126  | 0.3084          | 0.8722   |
| 0.3024        | 3.0   | 4689  | 0.2950          | 0.8797   |
| 0.2932        | 4.0   | 6252  | 0.2907          | 0.8820   |
| 0.2784        | 5.0   | 7815  | 0.2887          | 0.8838   |
| 0.2817        | 6.0   | 9378  | 0.2833          | 0.8859   |
| 0.2755        | 7.0   | 10941 | 0.2848          | 0.8860   |
| 0.2714        | 8.0   | 12504 | 0.2819          | 0.8866   |
| 0.2727        | 9.0   | 14067 | 0.2832          | 0.8871   |
| 0.2795        | 10.0  | 15630 | 0.2832          | 0.8872   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.14.0