---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 16class_800_newtest_xlm_robt_24nov23_v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 16class_800_newtest_xlm_robt_24nov23_v1

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: 0.1151
- Accuracy: 0.9774

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8283        | 1.0   | 1529  | 0.6162          | 0.8168   |
| 0.5779        | 2.0   | 3058  | 0.3744          | 0.8873   |
| 0.4409        | 3.0   | 4587  | 0.2805          | 0.9229   |
| 0.359         | 4.0   | 6116  | 0.2288          | 0.9434   |
| 0.2794        | 5.0   | 7645  | 0.1791          | 0.9598   |
| 0.2564        | 6.0   | 9174  | 0.1564          | 0.9668   |
| 0.198         | 7.0   | 10703 | 0.1274          | 0.9733   |
| 0.1773        | 8.0   | 12232 | 0.1151          | 0.9774   |


### Framework versions

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