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xlm-roberta-base-NER-favsbot
This model is a fine-tuned version of xlm-roberta-base on the favsbot dataset. It achieves the following results on the evaluation set:
- Loss: 1.0572
- Precision: 0.5556
- Recall: 0.4722
- F1: 0.5105
- Accuracy: 0.6900
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 | 2.4303 | 0.1448 | 0.3556 | 0.2058 | 0.1855 |
| No log | 2.0 | 8 | 2.3220 | 0.1465 | 0.3556 | 0.2075 | 0.1991 |
| No log | 3.0 | 12 | 2.1842 | 0.2486 | 0.2389 | 0.2436 | 0.4593 |
| No log | 4.0 | 16 | 1.9552 | 0.4 | 0.0111 | 0.0216 | 0.4367 |
| No log | 5.0 | 20 | 1.6989 | 0.0 | 0.0 | 0.0 | 0.4321 |
| No log | 6.0 | 24 | 1.6532 | 0.5 | 0.0056 | 0.0110 | 0.4344 |
| No log | 7.0 | 28 | 1.5724 | 0.3649 | 0.15 | 0.2126 | 0.5045 |
| No log | 8.0 | 32 | 1.5164 | 0.3654 | 0.2111 | 0.2676 | 0.5271 |
| No log | 9.0 | 36 | 1.4448 | 0.4203 | 0.1611 | 0.2329 | 0.5090 |
| No log | 10.0 | 40 | 1.3922 | 0.4833 | 0.1611 | 0.2417 | 0.5158 |
| No log | 11.0 | 44 | 1.3409 | 0.5395 | 0.2278 | 0.3203 | 0.5498 |
| No log | 12.0 | 48 | 1.2831 | 0.5824 | 0.2944 | 0.3911 | 0.5950 |
| No log | 13.0 | 52 | 1.2269 | 0.5714 | 0.3556 | 0.4384 | 0.6335 |
| No log | 14.0 | 56 | 1.1766 | 0.5625 | 0.4 | 0.4675 | 0.6606 |
| No log | 15.0 | 60 | 1.1408 | 0.5540 | 0.4278 | 0.4828 | 0.6674 |
| No log | 16.0 | 64 | 1.1159 | 0.56 | 0.4667 | 0.5091 | 0.6810 |
| No log | 17.0 | 68 | 1.0908 | 0.5658 | 0.4778 | 0.5181 | 0.6855 |
| No log | 18.0 | 72 | 1.0722 | 0.5658 | 0.4778 | 0.5181 | 0.6923 |
| No log | 19.0 | 76 | 1.0615 | 0.5592 | 0.4722 | 0.5120 | 0.6900 |
| No log | 20.0 | 80 | 1.0572 | 0.5556 | 0.4722 | 0.5105 | 0.6900 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
