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: RobertaBaseProcessedDownsampledKeywordDropout
  results: []
---

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# RobertaBaseProcessedDownsampledKeywordDropout

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: 0.2807
- Accuracy: 0.8711
- F1: 0.4847
- Precision: 0.3908
- Recall: 0.6382

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5428        | 1.0   | 297  | 0.4049          | 0.9050   | 0.0    | 0.0       | 0.0    |
| 0.3735        | 2.0   | 595  | 0.2807          | 0.8711   | 0.4847 | 0.3908    | 0.6382 |
| 0.3458        | 2.99  | 891  | 0.3110          | 0.8567   | 0.4828 | 0.3675    | 0.7035 |


### Framework versions

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