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# xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test02

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: 0.4252
- Jaccard (sample): [0.5110803324099723, 0.28313253012048195, 0.0, 0.0, 0.06741573033707865, 0.027649769585253458, 0.16304347826086957, 0.0]
- Jaccard (macro): 0.1315
- Macro-precision: 0.2475
- Macro-recall: 0.2583
- Macro F1: 0.1973
- Micro F1: 0.3673
- Accuracy: 0.165

## 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  | 0.4653          | [0.4540094339622642, 0.0, 0.0, 0.0, 0.03597122302158273, 0.0, 0.2, 0.0]                                                  | 0.0862          | 0.1050          | 0.2127       | 0.1284   | 0.3099   | 0.1308   |
| No log        | 2.0   | 428  | 0.4350          | [0.525035765379113, 0.16226415094339622, 0.0, 0.0, 0.055944055944055944, 0.0, 0.1889400921658986, 0.0]                   | 0.1165          | 0.2048          | 0.2623       | 0.1739   | 0.3406   | 0.1525   |
| 0.4333        | 3.0   | 642  | 0.4252          | [0.5110803324099723, 0.28313253012048195, 0.0, 0.0, 0.06741573033707865, 0.027649769585253458, 0.16304347826086957, 0.0] | 0.1315          | 0.2475          | 0.2583       | 0.1973   | 0.3673   | 0.165    |


### 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-test02", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us