edos-2023-baseline-microsoft-deberta-v3-base-label_vector
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5524
- F1: 0.3162
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: 1e-05
- 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
- lr_scheduler_warmup_steps: 5
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
2.1209 | 1.18 | 100 | 1.9990 | 0.0801 |
1.7997 | 2.35 | 200 | 1.7293 | 0.1349 |
1.5749 | 3.53 | 300 | 1.6080 | 0.2431 |
1.3674 | 4.71 | 400 | 1.5411 | 0.2793 |
1.2214 | 5.88 | 500 | 1.5285 | 0.2980 |
1.0752 | 7.06 | 600 | 1.5165 | 0.3054 |
0.9899 | 8.24 | 700 | 1.5210 | 0.3186 |
0.8733 | 9.41 | 800 | 1.5385 | 0.3134 |
0.8578 | 10.59 | 900 | 1.5524 | 0.3162 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Downloads last month
- 15
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.