---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_Mixed-aug_insert_w2v-1
  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. -->

# xlm-roberta-base-Final_Mixed-aug_insert_w2v-1

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3222
- Accuracy: 0.75
- F1: 0.7494

## 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: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9974        | 1.0   | 86   | 0.7220          | 0.7      | 0.6853 |
| 0.6771        | 2.0   | 172  | 0.5830          | 0.75     | 0.7414 |
| 0.4881        | 3.0   | 258  | 0.7321          | 0.73     | 0.7233 |
| 0.3431        | 4.0   | 344  | 0.8026          | 0.76     | 0.7555 |
| 0.2209        | 5.0   | 430  | 0.9511          | 0.75     | 0.7443 |
| 0.1558        | 6.0   | 516  | 1.2518          | 0.72     | 0.7046 |
| 0.1311        | 7.0   | 602  | 1.2975          | 0.74     | 0.7397 |
| 0.1027        | 8.0   | 688  | 1.3222          | 0.75     | 0.7494 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3