safetensors generated_from_trainer base_model:roberta-base license:mit region:us
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: RobertaBaseProcessedDownsampledKeywordDropoutE7
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RobertaBaseProcessedDownsampledKeywordDropoutE7

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2529
- Accuracy: 0.8968
- F1: 0.4906
- Precision: 0.4622
- Recall: 0.5226

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 500
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4823        | 1.0   | 297  | 0.5612          | 0.6734   | 0.3346 | 0.2075    | 0.8643 |
| 0.3851        | 2.0   | 595  | 0.2529          | 0.8968   | 0.4906 | 0.4622    | 0.5226 |
| 0.3502        | 3.0   | 893  | 0.3441          | 0.8567   | 0.4898 | 0.3702    | 0.7236 |
| 0.438         | 4.0   | 1191 | 0.4888          | 0.7822   | 0.4314 | 0.2869    | 0.8693 |
| 0.2282        | 5.0   | 1488 | 0.6598          | 0.8247   | 0.4611 | 0.3257    | 0.7889 |
| 0.2487        | 6.0   | 1786 | 0.6865          | 0.8558   | 0.4864 | 0.3676    | 0.7186 |
| 0.0087        | 6.98  | 2079 | 0.8314          | 0.8481   | 0.4854 | 0.3580    | 0.7538 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
