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

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: 0.1980
- Macro-f1: 0.7336
- Micro-f1: 0.7898

## 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  | 0.1975          | 0.6393   | 0.7408   |
| 0.1811        | 2.0   | 564  | 0.1954          | 0.6541   | 0.7559   |
| 0.1811        | 3.0   | 846  | 0.1786          | 0.7063   | 0.7833   |
| 0.1167        | 4.0   | 1128 | 0.1746          | 0.7304   | 0.7928   |
| 0.1167        | 5.0   | 1410 | 0.1818          | 0.7270   | 0.7936   |
| 0.0921        | 6.0   | 1692 | 0.1933          | 0.7235   | 0.7810   |
| 0.0921        | 7.0   | 1974 | 0.1901          | 0.7326   | 0.7852   |
| 0.0721        | 8.0   | 2256 | 0.1980          | 0.7336   | 0.7898   |


### Framework versions

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