transformers pytorch xlm-roberta generated_from_trainer dataset:massive base_model:xlm-roberta-base license:mit endpoints_compatible region:us
---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
- f1
model-index:
- name: scenario-NON-KD-PR-COPY-D2_data-en-massive_all_1_1
  results: []
---

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# scenario-NON-KD-PR-COPY-D2_data-en-massive_all_1_1

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0539
- Accuracy: 0.4709
- F1: 0.4241

## 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: 44
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.0328        | 13.89 | 5000  | 3.6215          | 0.4636   | 0.4260 |
| 0.002         | 27.78 | 10000 | 4.0539          | 0.4709   | 0.4241 |


### Framework versions

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