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camembert-base-NER-favsbot
This model is a fine-tuned version of camembert-base on the favsbot dataset. It achieves the following results on the evaluation set:
- Loss: 1.7433
- Precision: 0.6
- Recall: 0.0121
- F1: 0.0238
- Accuracy: 0.4208
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: 1.5e-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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 2.2915 | 0.1364 | 0.1215 | 0.1285 | 0.3475 |
| No log | 2.0 | 8 | 2.2230 | 0.2909 | 0.0648 | 0.1060 | 0.4395 |
| No log | 3.0 | 12 | 2.1573 | 0.4545 | 0.0202 | 0.0388 | 0.4225 |
| No log | 4.0 | 16 | 2.0961 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 5.0 | 20 | 2.0426 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 6.0 | 24 | 1.9965 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 7.0 | 28 | 1.9575 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 8.0 | 32 | 1.9233 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 9.0 | 36 | 1.8933 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 10.0 | 40 | 1.8674 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 11.0 | 44 | 1.8441 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 12.0 | 48 | 1.8240 | 0.0 | 0.0 | 0.0 | 0.4123 |
| No log | 13.0 | 52 | 1.8060 | 1.0 | 0.0040 | 0.0081 | 0.4140 |
| No log | 14.0 | 56 | 1.7899 | 1.0 | 0.0040 | 0.0081 | 0.4140 |
| No log | 15.0 | 60 | 1.7762 | 1.0 | 0.0040 | 0.0081 | 0.4140 |
| No log | 16.0 | 64 | 1.7647 | 0.5 | 0.0040 | 0.0080 | 0.4157 |
| No log | 17.0 | 68 | 1.7556 | 0.5 | 0.0040 | 0.0080 | 0.4157 |
| No log | 18.0 | 72 | 1.7490 | 0.6667 | 0.0081 | 0.016 | 0.4174 |
| No log | 19.0 | 76 | 1.7449 | 0.75 | 0.0121 | 0.0239 | 0.4191 |
| No log | 20.0 | 80 | 1.7433 | 0.6 | 0.0121 | 0.0238 | 0.4208 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
