---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sentiment-5Epochs
  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. -->

# sentiment-5Epochs

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4947
- Accuracy: 0.8719
- F1: 0.8685
- Precision: 0.8919
- Recall: 0.8463

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3566        | 1.0   | 7088  | 0.3987          | 0.8627   | 0.8505 | 0.9336    | 0.7810 |
| 0.3468        | 2.0   | 14176 | 0.3861          | 0.8702   | 0.8638 | 0.9085    | 0.8232 |
| 0.335         | 3.0   | 21264 | 0.4421          | 0.8759   | 0.8697 | 0.9154    | 0.8283 |
| 0.3003        | 4.0   | 28352 | 0.4601          | 0.8754   | 0.8696 | 0.9119    | 0.8311 |
| 0.2995        | 5.0   | 35440 | 0.4947          | 0.8719   | 0.8685 | 0.8919    | 0.8463 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0
- Datasets 2.0.0
- Tokenizers 0.11.6