aleph_bert_gimmel-finetuned-ner
This model is a fine-tuned version of imvladikon/alephbertgimmel-base-512 on the nemo_corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.1231
- Precision: 0.8048
- Recall: 0.8059
- F1: 0.8054
- Accuracy: 0.9724
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.375 | 1.0 | 618 | 0.1505 | 0.7767 | 0.7590 | 0.7678 | 0.9660 |
0.1377 | 2.0 | 1236 | 0.1240 | 0.8188 | 0.8046 | 0.8116 | 0.9720 |
0.0967 | 3.0 | 1854 | 0.1231 | 0.8048 | 0.8059 | 0.8054 | 0.9724 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for msperka/aleph_bert_gimmel-finetuned-ner
Base model
imvladikon/alephbertgimmel-base-512Evaluation results
- Precision on nemo_corpusvalidation set self-reported0.805
- Recall on nemo_corpusvalidation set self-reported0.806
- F1 on nemo_corpusvalidation set self-reported0.805
- Accuracy on nemo_corpusvalidation set self-reported0.972