roberta-Questions-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: 0.3277
- Accuracy: 0.7702
- Precision: 0.2474
- Recall: 0.5663
- F1: 0.3443
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: 1.572007347885149e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.5054 | 1.0 | 136 | 0.3352 | 0.8306 | 0.2525 | 0.3012 | 0.2747 |
0.4132 | 2.0 | 272 | 0.3204 | 0.7856 | 0.22 | 0.3976 | 0.2833 |
0.3643 | 3.0 | 408 | 0.1676 | 0.8883 | 0.4545 | 0.2410 | 0.3150 |
0.3203 | 4.0 | 544 | 0.3204 | 0.7728 | 0.2473 | 0.5542 | 0.3420 |
0.2948 | 5.0 | 680 | 0.3277 | 0.7702 | 0.2474 | 0.5663 | 0.3443 |
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