---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base-downstream-ecthr-a
  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-ecthr-a

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: 0.2086
- Macro-f1: 0.6249
- Micro-f1: 0.6923

## 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: 16
- eval_batch_size: 16
- seed: 1
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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 | Validation Loss | Macro-f1 | Micro-f1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log        | 1.0   | 282  | 0.1788          | 0.5361   | 0.6691   |
| 0.1598        | 2.0   | 564  | 0.1657          | 0.5865   | 0.6876   |
| 0.1598        | 3.0   | 846  | 0.1847          | 0.6197   | 0.6803   |
| 0.1038        | 4.0   | 1128 | 0.1705          | 0.6383   | 0.6992   |
| 0.1038        | 5.0   | 1410 | 0.1813          | 0.6484   | 0.6948   |
| 0.0835        | 6.0   | 1692 | 0.1946          | 0.6427   | 0.6929   |
| 0.0835        | 7.0   | 1974 | 0.2086          | 0.6249   | 0.6923   |


### Framework versions

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