xmod-shared-roberta-base-legal-multi-downstream-ecthr-a
This model is a fine-tuned version of MHGanainy/xmod-shared-roberta-base-legal-multi on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2296
- Macro-f1: 0.6217
- Micro-f1: 0.6780
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 | 0.1815 | 0.5371 | 0.6695 |
0.1561 | 2.0 | 564 | 0.1618 | 0.5900 | 0.6909 |
0.1561 | 3.0 | 846 | 0.1860 | 0.6039 | 0.6832 |
0.1027 | 4.0 | 1128 | 0.1775 | 0.6361 | 0.7019 |
0.1027 | 5.0 | 1410 | 0.1779 | 0.6402 | 0.6927 |
0.0829 | 6.0 | 1692 | 0.2020 | 0.6182 | 0.6879 |
0.0829 | 7.0 | 1974 | 0.2296 | 0.6217 | 0.6780 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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