---
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-xlm-attempt2
  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-xlm-attempt2

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3637
- Accuracy: 0.87

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.07  | 50   | 0.4087          | 0.86     |
| No log        | 0.14  | 100  | 0.3930          | 0.86     |
| No log        | 0.21  | 150  | 0.4688          | 0.79     |
| No log        | 0.27  | 200  | 0.3834          | 0.82     |
| No log        | 0.34  | 250  | 0.4249          | 0.83     |
| No log        | 0.41  | 300  | 0.5777          | 0.8      |
| No log        | 0.48  | 350  | 0.4752          | 0.82     |
| No log        | 0.55  | 400  | 0.3080          | 0.89     |
| No log        | 0.62  | 450  | 0.4125          | 0.83     |
| 0.3475        | 0.68  | 500  | 0.3273          | 0.9      |
| 0.3475        | 0.75  | 550  | 0.6456          | 0.77     |
| 0.3475        | 0.82  | 600  | 0.6110          | 0.77     |
| 0.3475        | 0.89  | 650  | 0.3898          | 0.85     |
| 0.3475        | 0.96  | 700  | 0.4062          | 0.87     |
| 0.3475        | 1.03  | 750  | 0.3637          | 0.87     |


### Framework versions

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