
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xlm-roberta-base-finetuning-semeval-all-then-wrime-all-first-epoch3-test03

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: 0.4530
- Jaccard (sample): [0.5073529411764706, 0.24919093851132687, 0.0, 0.0, 0.04054054054054054, 0.009478672985781991, 0.19112627986348124, 0.0]
- Jaccard (macro): 0.1247
- Macro-precision: 0.3022
- Macro-recall: 0.3008
- Macro F1: 0.1862
- Micro F1: 0.3367
- Accuracy: 0.1508

## 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  | 0.4822          | [0.4949784791965567, 0.0, 0.0, 0.0, 0.021108179419525065, 0.0, 0.215, 0.0]                                               | 0.0914          | 0.1022          | 0.2798       | 0.1322   | 0.2856   | 0.1258   |
| No log        | 2.0   | 428  | 0.4663          | [0.5146579804560261, 0.1773049645390071, 0.0, 0.0, 0.030508474576271188, 0.0, 0.1797752808988764, 0.0]                   | 0.1128          | 0.1825          | 0.2856       | 0.1681   | 0.3030   | 0.135    |
| 0.4276        | 3.0   | 642  | 0.4530          | [0.5073529411764706, 0.24919093851132687, 0.0, 0.0, 0.04054054054054054, 0.009478672985781991, 0.19112627986348124, 0.0] | 0.1247          | 0.3022          | 0.3008       | 0.1862   | 0.3367   | 0.1508   |


### 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-test03", "results": []}]}
transformers tensorboard safetensors xlm-roberta text-classification generated_from_trainer base_model:xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us