---
base_model: finiteautomata/bertweet-base-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: finetuning-sentiment-model-1000-samples-synth
  results: []
---

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# finetuning-sentiment-model-1000-samples-synth

This model is a fine-tuned version of [finiteautomata/bertweet-base-sentiment-analysis](https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1326
- Accuracy: 0.9825
- F1: 0.9826
- Recall: 0.9705
- Precision: 0.9950

## 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: 2

### Training results



### Framework versions

- Transformers 4.39.3
- Pytorch 1.13.1+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2