---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-downstream-build_rr
  results: []
---

<!-- 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. -->

# roberta-base-downstream-build_rr

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:
- Precision: 0.1983
- Recall: 0.3587
- F1: 0.2554
- Micro-f1: 0.2554
- Accuracy: 0.9191
- Loss: 0.2640

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Precision | Recall | F1     | Micro-f1 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:---------:|:------:|:------:|:--------:|:--------:|:---------------:|
| No log        | 1.0   | 62   | 0.0835    | 0.1152 | 0.0968 | 0.0968   | 0.8780   | 0.4226          |
| No log        | 2.0   | 124  | 0.1537    | 0.2696 | 0.1957 | 0.1957   | 0.8931   | 0.3475          |
| No log        | 3.0   | 186  | 0.1875    | 0.3391 | 0.2415 | 0.2415   | 0.9052   | 0.2912          |
| No log        | 4.0   | 248  | 0.1992    | 0.3304 | 0.2486 | 0.2486   | 0.9003   | 0.2991          |
| No log        | 5.0   | 310  | 0.1784    | 0.3870 | 0.2442 | 0.2442   | 0.9066   | 0.2833          |
| No log        | 6.0   | 372  | 0.2206    | 0.3543 | 0.2719 | 0.2719   | 0.9148   | 0.2642          |
| No log        | 7.0   | 434  | 0.2300    | 0.3630 | 0.2816 | 0.2816   | 0.9177   | 0.2584          |
| No log        | 8.0   | 496  | 0.2179    | 0.3696 | 0.2742 | 0.2742   | 0.9177   | 0.2523          |
| 0.4245        | 9.0   | 558  | 0.1921    | 0.3696 | 0.2528 | 0.2528   | 0.9167   | 0.2630          |
| 0.4245        | 10.0  | 620  | 0.1983    | 0.3587 | 0.2554 | 0.2554   | 0.9191   | 0.2640          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1