---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-MARBERT-twitter-sentiment-Twitter
  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. -->

# Improved-MARBERT-twitter-sentiment-Twitter

This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7706
- Accuracy: 0.86

## 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: 1e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5838        | 0.55  | 50   | 0.6058          | 0.71     |
| 0.3547        | 1.1   | 100  | 0.3887          | 0.83     |
| 0.2792        | 1.65  | 150  | 0.3479          | 0.85     |
| 0.1929        | 2.2   | 200  | 0.3596          | 0.87     |
| 0.1725        | 2.75  | 250  | 0.5874          | 0.8      |
| 0.1342        | 3.3   | 300  | 0.6560          | 0.81     |
| 0.1179        | 3.85  | 350  | 0.5146          | 0.85     |
| 0.079         | 4.4   | 400  | 0.6173          | 0.83     |
| 0.0928        | 4.95  | 450  | 0.7558          | 0.81     |
| 0.0425        | 5.49  | 500  | 1.0791          | 0.77     |
| 0.0609        | 6.04  | 550  | 0.7408          | 0.85     |
| 0.0328        | 6.59  | 600  | 0.8294          | 0.82     |
| 0.0531        | 7.14  | 650  | 0.6755          | 0.86     |
| 0.0342        | 7.69  | 700  | 0.6880          | 0.86     |
| 0.0263        | 8.24  | 750  | 0.7326          | 0.86     |
| 0.0147        | 8.79  | 800  | 0.8116          | 0.85     |
| 0.0169        | 9.34  | 850  | 0.8261          | 0.86     |
| 0.0118        | 9.89  | 900  | 0.7473          | 0.88     |
| 0.0087        | 10.44 | 950  | 0.7959          | 0.86     |
| 0.0051        | 10.99 | 1000 | 0.8585          | 0.85     |
| 0.0086        | 11.54 | 1050 | 0.8035          | 0.87     |
| 0.0076        | 12.09 | 1100 | 0.8838          | 0.84     |
| 0.0048        | 12.64 | 1150 | 0.8124          | 0.87     |
| 0.0095        | 13.19 | 1200 | 0.9262          | 0.85     |
| 0.0024        | 13.74 | 1250 | 0.8280          | 0.86     |
| 0.0109        | 14.29 | 1300 | 0.7895          | 0.87     |
| 0.0038        | 14.84 | 1350 | 0.7706          | 0.86     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1