roberta-Empathy-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: 0.1959
- Accuracy: 0.8691
- Precision: 0.3387
- Recall: 0.2561
- F1: 0.2917
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: 1.7040925846794196e-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 |
---|---|---|---|---|---|---|---|
0.4468 | 1.0 | 140 | 0.3926 | 0.8703 | 0.3582 | 0.2927 | 0.3221 |
0.3624 | 2.0 | 280 | 0.2036 | 0.8755 | 0.3333 | 0.1829 | 0.2362 |
0.3061 | 3.0 | 420 | 0.1371 | 0.8973 | 0.75 | 0.0366 | 0.0698 |
0.2535 | 4.0 | 560 | 0.1825 | 0.8768 | 0.375 | 0.2561 | 0.3043 |
0.2381 | 5.0 | 700 | 0.1959 | 0.8691 | 0.3387 | 0.2561 | 0.2917 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
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Base model
FacebookAI/roberta-large