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# xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test04

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: 0.4398
- Jaccard (sample): [0.5233785822021116, 0.29936305732484075, 0.0, 0.0, 0.058823529411764705, 0.0776255707762557, 0.19844357976653695, 0.0]
- Jaccard (macro): 0.1447
- Macro-precision: 0.2740
- Macro-recall: 0.3252
- Macro F1: 0.2168
- Micro F1: 0.3651
- Accuracy: 0.1617

## 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  | 0.4668          | [0.5083179297597042, 0.0, 0.0, 0.0, 0.0423728813559322, 0.0, 0.2147887323943662, 0.0]                                   | 0.0957          | 0.1276          | 0.2565       | 0.1386   | 0.2697   | 0.1308   |
| No log        | 2.0   | 428  | 0.4372          | [0.526148969889065, 0.25483870967741934, 0.0, 0.0, 0.06428571428571428, 0.07555555555555556, 0.2062780269058296, 0.0]   | 0.1409          | 0.2628          | 0.2967       | 0.2124   | 0.3561   | 0.1608   |
| 0.4205        | 3.0   | 642  | 0.4398          | [0.5233785822021116, 0.29936305732484075, 0.0, 0.0, 0.058823529411764705, 0.0776255707762557, 0.19844357976653695, 0.0] | 0.1447          | 0.2740          | 0.3252       | 0.2168   | 0.3651   | 0.1617   |


### 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-test04", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us