roberta-cbl-Suggestions-badareas-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: 0.9014
- Accuracy: 0.8986
- Precision: 0.4563
- Recall: 0.6714
- F1: 0.5434
Model description
More information needed
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: 6.8833080998543704e-06
- train_batch_size: 8
- 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 |
---|---|---|---|---|---|---|---|
0.7113 | 1.0 | 972 | 0.6564 | 0.9114 | 0.5135 | 0.2714 | 0.3551 |
0.6092 | 2.0 | 1944 | 0.5768 | 0.8768 | 0.4 | 0.7429 | 0.52 |
0.4753 | 3.0 | 2916 | 0.5549 | 0.8947 | 0.45 | 0.7714 | 0.5684 |
0.3467 | 4.0 | 3888 | 0.8058 | 0.8999 | 0.46 | 0.6571 | 0.5412 |
0.2434 | 5.0 | 4860 | 0.9014 | 0.8986 | 0.4563 | 0.6714 | 0.5434 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
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Base model
FacebookAI/roberta-large