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---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: deberta-v3-base_conll03
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-v3-base_conll03
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- F1-type-match: 0.9316
- F1-partial: 0.9733
- F1-strict: 0.9235
- F1-exact: 0.9651
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1-type-match | F1-partial | F1-strict | F1-exact |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:|
| 0.0963 | 1.0 | 439 | 0.0814 | 0.8408 | 0.8897 | 0.8323 | 0.8809 |
| 0.0197 | 2.0 | 878 | 0.0803 | 0.9219 | 0.9725 | 0.9138 | 0.9648 |
| 0.0108 | 3.0 | 1317 | 0.0858 | 0.9307 | 0.9728 | 0.9228 | 0.9648 |
| 0.0054 | 4.0 | 1756 | 0.0922 | 0.9313 | 0.9725 | 0.9235 | 0.9643 |
| 0.0033 | 5.0 | 2195 | 0.0973 | 0.9316 | 0.9733 | 0.9235 | 0.9651 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
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