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# results

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.9243
- eval_accuracy: 0.1677
- eval_f1: 0.0482
- eval_precision: 0.0281
- eval_recall: 0.1677
- eval_runtime: 27.8461
- eval_samples_per_second: 41.334
- eval_steps_per_second: 10.343
- epoch: 2.0
- step: 3064

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "base_model": "xlm-roberta-large", "model-index": [{"name": "results", "results": []}]}
transformers safetensors xlm-roberta text-classification generated_from_trainer base_model:xlm-roberta-large license:mit autotrain_compatible endpoints_compatible region:us