metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base-downstream-ecthr-a
results: []
roberta-base-downstream-ecthr-a
This model is a fine-tuned version of 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