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roberta-base-finetuned-recruitment-exp
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1044
- Precision: 0.7320
- Recall: 0.8560
- F1: 0.7892
- Accuracy: 0.9713
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 17 | 0.4051 | 0.25 | 0.0061 | 0.0119 | 0.8984 |
| No log | 2.0 | 34 | 0.2450 | 0.4040 | 0.3732 | 0.3880 | 0.9280 |
| No log | 3.0 | 51 | 0.1481 | 0.5385 | 0.6663 | 0.5956 | 0.9555 |
| No log | 4.0 | 68 | 0.1269 | 0.6295 | 0.7961 | 0.7031 | 0.964 |
| No log | 5.0 | 85 | 0.1101 | 0.6639 | 0.8235 | 0.7352 | 0.9679 |
| No log | 6.0 | 102 | 0.1116 | 0.7287 | 0.7819 | 0.7544 | 0.9701 |
| No log | 7.0 | 119 | 0.1160 | 0.7026 | 0.8266 | 0.7596 | 0.9684 |
| No log | 8.0 | 136 | 0.1071 | 0.7442 | 0.8499 | 0.7936 | 0.9717 |
| No log | 9.0 | 153 | 0.1044 | 0.7320 | 0.8560 | 0.7892 | 0.9713 |
| No log | 10.0 | 170 | 0.1081 | 0.7532 | 0.8448 | 0.7964 | 0.9722 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
