
<!-- 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. -->

# scenario-non-kd-from-pre-finetune-div-2-data-tweet_eval-sentiment-model-xlm-robe

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1325
- Accuracy: 0.719
- F1: 0.7031

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.7134        | 0.7   | 1000  | 0.7244          | 0.6775   | 0.5751 |
| 0.6266        | 1.4   | 2000  | 0.6651          | 0.7085   | 0.6909 |
| 0.5964        | 2.1   | 3000  | 0.7115          | 0.72     | 0.6987 |
| 0.5437        | 2.81  | 4000  | 0.6681          | 0.714    | 0.7014 |
| 0.4591        | 3.51  | 5000  | 0.7522          | 0.7215   | 0.7032 |
| 0.4024        | 4.21  | 6000  | 0.8147          | 0.705    | 0.6909 |
| 0.3932        | 4.91  | 7000  | 0.8027          | 0.7105   | 0.6980 |
| 0.3219        | 5.61  | 8000  | 0.7793          | 0.7145   | 0.6871 |
| 0.2568        | 6.31  | 9000  | 1.0096          | 0.706    | 0.6932 |
| 0.2771        | 7.01  | 10000 | 1.0199          | 0.7075   | 0.6899 |
| 0.2338        | 7.71  | 11000 | 1.0736          | 0.702    | 0.6877 |
| 0.1869        | 8.42  | 12000 | 1.1162          | 0.706    | 0.6877 |
| 0.1881        | 9.12  | 13000 | 1.3118          | 0.708    | 0.6851 |
| 0.1761        | 9.82  | 14000 | 1.3011          | 0.6975   | 0.6776 |
| 0.157         | 10.52 | 15000 | 1.1325          | 0.719    | 0.7031 |


### 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": ["tweet_eval"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-non-kd-from-pre-finetune-div-2-data-tweet_eval-sentiment-model-xlm-robe", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:tweet_eval base_model:xlm-roberta-base license:mit endpoints_compatible region:us