---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
datasets:
- ontonotes5
model-index:
- name: deberta-v3-base_on5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-v3-base_on5

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the ontonotes5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0598
- F1-type-match: 0.6780
- F1-partial: 0.6872
- F1-strict: 0.6565
- F1-exact: 0.6729

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 | F1-type-match | F1-partial | F1-strict | F1-exact |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:|
| 0.0738        | 1.0   | 936  | 0.0624          | 0.5568        | 0.5632     | 0.5322    | 0.5479   |
| 0.0432        | 2.0   | 1873 | 0.0591          | 0.5773        | 0.5848     | 0.5559    | 0.5709   |
| 0.0289        | 3.0   | 2808 | 0.0598          | 0.6780        | 0.6872     | 0.6565    | 0.6729   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0