roberta-Structure-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
This model is a fine-tuned version of FacebookAI/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1962
- Accuracy: 0.9127
- Precision: 0.4457
- Recall: 0.7069
- F1: 0.5467
Model description
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Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4.253164784470222e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.3038 | 1.0 | 167 | 0.2109 | 0.9089 | 0.3898 | 0.3966 | 0.3932 |
0.2729 | 2.0 | 334 | 0.2530 | 0.9012 | 0.4078 | 0.7241 | 0.5217 |
0.243 | 3.0 | 501 | 0.2277 | 0.9114 | 0.4409 | 0.7069 | 0.5430 |
0.2129 | 4.0 | 668 | 0.1612 | 0.9204 | 0.4767 | 0.7069 | 0.5694 |
0.1673 | 5.0 | 835 | 0.1962 | 0.9127 | 0.4457 | 0.7069 | 0.5467 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
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Base model
FacebookAI/roberta-large