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# xlm-roberta-base-finetuning-wrime-random4000-epoch6-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: 0.3173
- Jaccard (sample): [0.591182364729459, 0.3438395415472779, 0.6059322033898306, 0.036, 0.0, 0.14396887159533073, 0.1870967741935484, 0.0]
- Jaccard (macro): 0.2385
- Macro-precision: 0.4548
- Macro-recall: 0.2914
- Macro F1: 0.3307
- Micro F1: 0.5504
- Accuracy: 0.3125

## 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: 6
- 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   | 125  | 0.4209          | [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]                                                                                             | 0.0             | 0.0             | 0.0          | 0.0      | 0.0      | 0.0775   |
| No log        | 2.0   | 250  | 0.3810          | [0.014084507042253521, 0.03816793893129771, 0.0, 0.0, 0.0, 0.004739336492890996, 0.0, 0.0]                                           | 0.0071          | 0.2821          | 0.0074       | 0.0138   | 0.0194   | 0.0792   |
| No log        | 3.0   | 375  | 0.3545          | [0.5387323943661971, 0.271523178807947, 0.3476190476190476, 0.0, 0.0, 0.0047169811320754715, 0.016260162601626018, 0.0]              | 0.1474          | 0.4623          | 0.1790       | 0.2106   | 0.4353   | 0.2475   |
| 0.4439        | 4.0   | 500  | 0.3286          | [0.5519848771266541, 0.3492957746478873, 0.5913978494623656, 0.0, 0.0, 0.155893536121673, 0.1310344827586207, 0.0]                   | 0.2225          | 0.3752          | 0.2767       | 0.3092   | 0.5339   | 0.2983   |
| 0.4439        | 5.0   | 625  | 0.3213          | [0.599271402550091, 0.3089171974522293, 0.5960698689956332, 0.10384615384615385, 0.0, 0.09691629955947137, 0.12857142857142856, 0.0] | 0.2292          | 0.4834          | 0.2749       | 0.3201   | 0.5519   | 0.3233   |
| 0.4439        | 6.0   | 750  | 0.3173          | [0.591182364729459, 0.3438395415472779, 0.6059322033898306, 0.036, 0.0, 0.14396887159533073, 0.1870967741935484, 0.0]                | 0.2385          | 0.4548          | 0.2914       | 0.3307   | 0.5504   | 0.3125   |


### Framework versions

- Transformers 4.35.2
- 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-wrime-random4000-epoch6-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