metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-on-custom-kural-500
results: []
mdeberta-v3-base-on-custom-kural-500
This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4313
- Accuracy: 0.8133
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 22 | 0.5663 | 0.74 |
No log | 2.0 | 44 | 0.5780 | 0.74 |
No log | 3.0 | 66 | 0.5738 | 0.74 |
No log | 4.0 | 88 | 0.5953 | 0.74 |
No log | 5.0 | 110 | 0.5955 | 0.74 |
No log | 6.0 | 132 | 0.5311 | 0.74 |
No log | 7.0 | 154 | 0.5937 | 0.74 |
No log | 8.0 | 176 | 0.4819 | 0.84 |
No log | 9.0 | 198 | 0.4305 | 0.8333 |
No log | 10.0 | 220 | 0.4313 | 0.8133 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2