---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 16class_all9k_promptcor_23nov23_xlm_robt_case
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 16class_all9k_promptcor_23nov23_xlm_robt_case

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: 0.1020
- Accuracy: 0.9787

## 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: 1e-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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0707        | 1.0   | 1442  | 0.5981          | 0.8113   |
| 0.5897        | 2.0   | 2884  | 0.3605          | 0.8954   |
| 0.4212        | 3.0   | 4326  | 0.2835          | 0.9249   |
| 0.3463        | 4.0   | 5768  | 0.2020          | 0.9498   |
| 0.2749        | 5.0   | 7210  | 0.1751          | 0.9594   |
| 0.2336        | 6.0   | 8652  | 0.1298          | 0.9716   |
| 0.1906        | 7.0   | 10094 | 0.1186          | 0.9759   |
| 0.1458        | 8.0   | 11536 | 0.1020          | 0.9787   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0