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# scenario-kd-from-pre-finetune-gold-silver-div-2-data-tyqiangz-multilingual-senti

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the multilingual-sentiments dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9561
- Accuracy: 0.2562
- F1: 0.2365

## 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: 5e-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
- num_epochs: 6969

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
| 3.1636        | 17.24  | 1000  | 4.0259          | 0.2963   | 0.2386 |
| 2.9584        | 34.48  | 2000  | 4.0043          | 0.2932   | 0.2520 |
| 2.8957        | 51.72  | 3000  | 3.9887          | 0.2870   | 0.2529 |
| 2.8681        | 68.97  | 4000  | 3.9818          | 0.2747   | 0.2494 |
| 2.8441        | 86.21  | 5000  | 3.9595          | 0.2901   | 0.2565 |
| 2.8338        | 103.45 | 6000  | 4.0413          | 0.2870   | 0.2596 |
| 2.8219        | 120.69 | 7000  | 4.0289          | 0.2840   | 0.2654 |
| 2.8123        | 137.93 | 8000  | 3.9893          | 0.2809   | 0.2576 |
| 2.8089        | 155.17 | 9000  | 3.9519          | 0.2654   | 0.2370 |
| 2.8016        | 172.41 | 10000 | 3.9725          | 0.2654   | 0.2402 |
| 2.7981        | 189.66 | 11000 | 3.9249          | 0.2716   | 0.2423 |
| 2.7971        | 206.9  | 12000 | 3.9656          | 0.2562   | 0.2272 |
| 2.7922        | 224.14 | 13000 | 4.0050          | 0.2593   | 0.2379 |
| 2.7863        | 241.38 | 14000 | 3.9745          | 0.2685   | 0.2390 |
| 2.7871        | 258.62 | 15000 | 3.9207          | 0.2593   | 0.2350 |
| 2.782         | 275.86 | 16000 | 3.9141          | 0.2809   | 0.2467 |
| 2.7733        | 293.1  | 17000 | 3.9561          | 0.2562   | 0.2365 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["multilingual-sentiments"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-kd-from-pre-finetune-gold-silver-div-2-data-tyqiangz-multilingual-senti", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:multilingual-sentiments base_model:xlm-roberta-base license:mit endpoints_compatible region:us