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# xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test01

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: 0.4347
- Jaccard (sample): [0.5185185185185185, 0.32122905027932963, 0.0, 0.0, 0.04316546762589928, 0.0, 0.18502202643171806, 0.0]
- Jaccard (macro): 0.1335
- Macro-precision: 0.1781
- Macro-recall: 0.2720
- Macro F1: 0.1955
- Micro F1: 0.3633
- Accuracy: 0.1642

## 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: 32
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Jaccard (sample)                                                                                        | Jaccard (macro) | Macro-precision | Macro-recall | Macro F1 | Micro F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------:|:---------------:|:---------------:|:------------:|:--------:|:--------:|:--------:|
| No log        | 1.0   | 214  | 0.4568          | [0.5042134831460674, 0.0, 0.0, 0.0, 0.03888888888888889, 0.0, 0.2100456621004566, 0.0]                  | 0.0941          | 0.1149          | 0.2319       | 0.1366   | 0.3072   | 0.14     |
| No log        | 2.0   | 428  | 0.4436          | [0.5313531353135313, 0.23825503355704697, 0.0, 0.0, 0.0440251572327044, 0.0, 0.1975806451612903, 0.0]   | 0.1264          | 0.1936          | 0.2600       | 0.1866   | 0.3361   | 0.155    |
| 0.4304        | 3.0   | 642  | 0.4347          | [0.5185185185185185, 0.32122905027932963, 0.0, 0.0, 0.04316546762589928, 0.0, 0.18502202643171806, 0.0] | 0.1335          | 0.1781          | 0.2720       | 0.1955   | 0.3633   | 0.1642   |


### Framework versions

- Transformers 4.36.1
- Pytorch 1.13.0
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "xlm-roberta-base", "model-index": [{"name": "xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test01", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us