---
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-azsci-topics
  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-large-azsci-topics

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4012
- Precision: 0.9115
- Recall: 0.9158
- F1: 0.9121
- Accuracy: 0.9158

## 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: 64
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 288  | 0.6402          | 0.8063    | 0.8073 | 0.7900 | 0.8073   |
| 1.0792        | 2.0   | 576  | 0.4482          | 0.8827    | 0.8776 | 0.8743 | 0.8776   |
| 1.0792        | 3.0   | 864  | 0.3947          | 0.8968    | 0.9019 | 0.8977 | 0.9019   |
| 0.3135        | 4.0   | 1152 | 0.4177          | 0.9043    | 0.9080 | 0.9047 | 0.9080   |
| 0.3135        | 5.0   | 1440 | 0.4012          | 0.9115    | 0.9158 | 0.9121 | 0.9158   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2