distilbert-NER-LinearAlg-finetuned
This model is a fine-tuned version of dslim/distilbert-NER on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0947
- F1 Score: 0.9014
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 Score |
---|---|---|---|---|
0.3042 | 1.0 | 222 | 0.2354 | 0.6871 |
0.1657 | 2.0 | 444 | 0.1603 | 0.7853 |
0.0996 | 3.0 | 666 | 0.1257 | 0.8369 |
0.0656 | 4.0 | 888 | 0.1090 | 0.8604 |
0.0401 | 5.0 | 1110 | 0.1052 | 0.8691 |
0.0321 | 6.0 | 1332 | 0.0986 | 0.8886 |
0.0246 | 7.0 | 1554 | 0.0952 | 0.8980 |
0.017 | 8.0 | 1776 | 0.0980 | 0.8967 |
0.017 | 9.0 | 1998 | 0.0944 | 0.9012 |
0.0143 | 10.0 | 2220 | 0.0947 | 0.9014 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for Heather-Driver/distilbert-NER-LinearAlg-finetuned
Base model
distilbert/distilbert-base-cased
Quantized
dslim/distilbert-NER