chem_ner_scratch
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0897
- Precision: 0.9527
- Recall: 0.9620
- F1: 0.9566
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
---|---|---|---|---|---|---|
2.0777 | 0.9873 | 39 | 0.9136 | 0.3364 | 0.3755 | 0.3192 |
2.0777 | 2.0 | 79 | 0.2245 | 0.8922 | 0.8075 | 0.8391 |
0.8865 | 2.9620 | 117 | 0.0897 | 0.9527 | 0.9620 | 0.9566 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for muratti18462/chem_ner_scratch
Base model
microsoft/deberta-v3-base