metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: pd_tg
results: []
pd_tg
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3292
- Accuracy: 0.8976
- F1: 0.9033
- Precision: 0.8986
- Recall: 0.9079
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 55 | 0.6494 | 0.6283 | 0.7935 | 0.7082 | 0.9022 |
| No log | 2.0 | 110 | 0.4126 | 0.8262 | 0.8262 | 0.8262 | 0.8262 |
| No log | 3.0 | 165 | 0.3292 | 0.8976 | 0.9033 | 0.8986 | 0.9079 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1