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--- |
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library_name: transformers |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: roberta-base-downstream-ecthr-a |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta-base-downstream-ecthr-a |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2086 |
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- Macro-f1: 0.6249 |
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- Micro-f1: 0.6923 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 1 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Macro-f1 | Micro-f1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| No log | 1.0 | 282 | 0.1788 | 0.5361 | 0.6691 | |
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| 0.1598 | 2.0 | 564 | 0.1657 | 0.5865 | 0.6876 | |
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| 0.1598 | 3.0 | 846 | 0.1847 | 0.6197 | 0.6803 | |
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| 0.1038 | 4.0 | 1128 | 0.1705 | 0.6383 | 0.6992 | |
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| 0.1038 | 5.0 | 1410 | 0.1813 | 0.6484 | 0.6948 | |
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| 0.0835 | 6.0 | 1692 | 0.1946 | 0.6427 | 0.6929 | |
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| 0.0835 | 7.0 | 1974 | 0.2086 | 0.6249 | 0.6923 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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