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# checkpoints_xnli

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xnli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4345
- Accuracy: 0.8473

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4929        | 1.0   | 11045 | 0.4551          | 0.8217   |
| 0.408         | 2.0   | 22090 | 0.4308          | 0.8358   |
| 0.3093        | 3.0   | 33135 | 0.4345          | 0.8473   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xnli"], "metrics": ["accuracy"], "base_model": "xlm-roberta-base", "model-index": [{"name": "checkpoints_xnli", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "xnli", "type": "xnli", "config": "en", "split": "train", "args": "en"}, "metrics": [{"type": "accuracy", "value": 0.8472664306994984, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer dataset:xnli base_model:xlm-roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us