transformers pytorch xlm-roberta generated_from_trainer dataset:massive base_model:FacebookAI/xlm-roberta-base license:mit endpoints_compatible region:us
---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
- f1
model-index:
- name: scenario-KD-SCR-MSV-CL-D2-data-cl-massive-all_1.1
  results: []
---

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# scenario-KD-SCR-MSV-CL-D2-data-cl-massive-all_1.1

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 10.0486
- Accuracy: 0.1816
- F1: 0.1758

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 99
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 4.246         | 0.56  | 5000  | 8.6110          | 0.1591   | 0.1441 |
| 2.6928        | 1.11  | 10000 | 8.9880          | 0.1776   | 0.1736 |
| 2.3303        | 1.67  | 15000 | 8.7526          | 0.1875   | 0.1820 |
| 1.812         | 2.22  | 20000 | 9.0346          | 0.1882   | 0.1804 |
| 1.6981        | 2.78  | 25000 | 9.2768          | 0.1868   | 0.1818 |
| 1.3869        | 3.33  | 30000 | 10.0564         | 0.1805   | 0.1774 |
| 1.3492        | 3.89  | 35000 | 9.7433          | 0.1804   | 0.1739 |
| 1.1196        | 4.45  | 40000 | 10.0486         | 0.1816   | 0.1758 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
