---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-finetuned-emotion-2-labels
  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-finetuned-emotion-2-labels

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: 1.1200
- Accuracy: 0.835
- F1: 0.8335

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6973        | 1.0   | 25   | 0.6917          | 0.5      | 0.3333 |
| 0.6626        | 2.0   | 50   | 0.5690          | 0.745    | 0.7431 |
| 0.5392        | 3.0   | 75   | 0.4598          | 0.76     | 0.7591 |
| 0.4253        | 4.0   | 100  | 0.4313          | 0.8      | 0.7993 |
| 0.2973        | 5.0   | 125  | 0.5872          | 0.795    | 0.7906 |
| 0.2327        | 6.0   | 150  | 0.4951          | 0.805    | 0.8049 |
| 0.173         | 7.0   | 175  | 0.6095          | 0.815    | 0.8142 |
| 0.1159        | 8.0   | 200  | 0.6523          | 0.825    | 0.8246 |
| 0.0791        | 9.0   | 225  | 0.6651          | 0.825    | 0.8243 |
| 0.0557        | 10.0  | 250  | 0.8242          | 0.83     | 0.8286 |
| 0.0643        | 11.0  | 275  | 0.6710          | 0.825    | 0.8243 |
| 0.0507        | 12.0  | 300  | 0.7729          | 0.83     | 0.8294 |
| 0.0239        | 13.0  | 325  | 0.8618          | 0.83     | 0.8283 |
| 0.0107        | 14.0  | 350  | 0.9683          | 0.835    | 0.8335 |
| 0.0233        | 15.0  | 375  | 1.0850          | 0.825    | 0.8227 |
| 0.0134        | 16.0  | 400  | 0.9801          | 0.835    | 0.8343 |
| 0.0122        | 17.0  | 425  | 1.0427          | 0.845    | 0.8439 |
| 0.0046        | 18.0  | 450  | 1.0867          | 0.84     | 0.8387 |
| 0.0038        | 19.0  | 475  | 1.0950          | 0.83     | 0.8289 |
| 0.002         | 20.0  | 500  | 1.1200          | 0.835    | 0.8335 |


### Framework versions

- Transformers 4.19.0
- Pytorch 1.12.0+cu113
- Datasets 1.16.1
- Tokenizers 0.12.1
