metadata
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
metrics:
- recall
- precision
model-index:
- name: deberta-v3-xsmall-finetuned-ner-1024
results: []
deberta-v3-xsmall-finetuned-ner-1024
This model is a fine-tuned version of microsoft/deberta-v3-xsmall on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1799
- Recall: 0.0
- Precision: 0.0
- Fbeta Score: nan
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: 0.0013
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | Fbeta Score |
|---|---|---|---|---|---|---|
| 0.1644 | 1.0 | 4496 | 0.1353 | 0.0 | 0.0 | nan |
| 0.1576 | 2.0 | 8992 | 0.1371 | 0.0 | 0.0 | nan |
| 0.1728 | 3.0 | 13488 | 0.2194 | 0.0 | 0.0 | nan |
| 0.1422 | 4.0 | 17984 | 0.1799 | 0.0 | 0.0 | nan |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1