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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: roberta-large-aces
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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-large-aces
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5257
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- Precision: 0.8561
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- Recall: 0.8594
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- F1: 0.8553
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- Accuracy: 0.8594
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- F1 Who: 0.8494
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- F1 What: 0.8391
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- F1 Where: 0.7558
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- F1 How: 0.9208
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | F1 Who | F1 What | F1 Where | F1 How |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:------:|:-------:|:--------:|:------:|
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| 0.4619 | 1.0 | 87 | 0.5447 | 0.8247 | 0.8416 | 0.8308 | 0.8416 | 0.8309 | 0.8188 | 0.6973 | 0.9244 |
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| 0.4358 | 2.0 | 174 | 0.4662 | 0.8522 | 0.8571 | 0.8517 | 0.8571 | 0.8314 | 0.8446 | 0.7613 | 0.9238 |
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| 0.3793 | 3.0 | 261 | 0.4892 | 0.8507 | 0.8622 | 0.8556 | 0.8622 | 0.8321 | 0.8418 | 0.7725 | 0.9280 |
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| 0.2875 | 4.0 | 348 | 0.5034 | 0.8702 | 0.8641 | 0.8593 | 0.8641 | 0.8471 | 0.8441 | 0.7715 | 0.9225 |
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| 0.1847 | 5.0 | 435 | 0.5257 | 0.8561 | 0.8594 | 0.8553 | 0.8594 | 0.8494 | 0.8391 | 0.7558 | 0.9208 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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