roberta-base-legal-multi-downstream-ecthr-a
This model is a fine-tuned version of MHGanainy/roberta-base-legal-multi on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2055
- Macro-f1: 0.6339
- Micro-f1: 0.6926
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 | 0.1810 | 0.5535 | 0.6674 |
0.1548 | 2.0 | 564 | 0.1590 | 0.5891 | 0.6939 |
0.1548 | 3.0 | 846 | 0.1716 | 0.6243 | 0.6943 |
0.1015 | 4.0 | 1128 | 0.1635 | 0.6352 | 0.7074 |
0.1015 | 5.0 | 1410 | 0.1629 | 0.6666 | 0.7113 |
0.0807 | 6.0 | 1692 | 0.1878 | 0.6233 | 0.6906 |
0.0807 | 7.0 | 1974 | 0.1939 | 0.6427 | 0.6932 |
0.0618 | 8.0 | 2256 | 0.2055 | 0.6339 | 0.6926 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
MHGanainy/roberta-base-legal-multi