|
--- |
|
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 |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 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: 0.0776 |
|
- F1-type-match: 0.9325 |
|
- F1-partial: 0.9488 |
|
- F1-strict: 0.9046 |
|
- F1-exact: 0.9299 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:| |
|
| 0.0427 | 1.0 | 936 | 0.0674 | 0.9291 | 0.9452 | 0.8986 | 0.9246 | |
|
| 0.0235 | 2.0 | 1873 | 0.0722 | 0.9281 | 0.9464 | 0.9002 | 0.9275 | |
|
| 0.0148 | 3.0 | 2808 | 0.0776 | 0.9325 | 0.9488 | 0.9046 | 0.9299 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.15.0 |
|
|
