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roberta-base-finetuned-recruitment-eval-2
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1002
- Precision: 0.8023
- Recall: 0.8531
- F1: 0.8269
- Accuracy: 0.9760
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 15 | 0.3547 | 0.0 | 0.0 | 0.0 | 0.9127 |
No log | 2.0 | 30 | 0.2395 | 0.3442 | 0.2978 | 0.3194 | 0.9305 |
No log | 3.0 | 45 | 0.1640 | 0.5315 | 0.6253 | 0.5746 | 0.9576 |
No log | 4.0 | 60 | 0.1231 | 0.6518 | 0.7871 | 0.7131 | 0.9606 |
No log | 5.0 | 75 | 0.1076 | 0.7409 | 0.8208 | 0.7788 | 0.9708 |
No log | 6.0 | 90 | 0.1220 | 0.6817 | 0.8342 | 0.7503 | 0.9658 |
No log | 7.0 | 105 | 0.1030 | 0.7850 | 0.8167 | 0.8005 | 0.9757 |
No log | 8.0 | 120 | 0.1053 | 0.7769 | 0.8167 | 0.7963 | 0.9745 |
No log | 9.0 | 135 | 0.1002 | 0.8023 | 0.8531 | 0.8269 | 0.9760 |
No log | 10.0 | 150 | 0.1100 | 0.7689 | 0.8477 | 0.8064 | 0.9724 |
No log | 11.0 | 165 | 0.1061 | 0.7757 | 0.8531 | 0.8126 | 0.9731 |
No log | 12.0 | 180 | 0.1081 | 0.7748 | 0.8531 | 0.8121 | 0.9734 |
No log | 13.0 | 195 | 0.1095 | 0.7761 | 0.8504 | 0.8116 | 0.9737 |
No log | 14.0 | 210 | 0.1124 | 0.7800 | 0.8504 | 0.8137 | 0.9743 |
No log | 15.0 | 225 | 0.1117 | 0.7800 | 0.8504 | 0.8137 | 0.9746 |
Framework versions
- Transformers 4.27.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3