metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ops_subcate
results: []
ops_subcate
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: 0.1325
- Accuracy: 0.7228
- F1: 0.7556
- Precision: 0.7866
- Recall: 0.7270
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: 128
- 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 49 | 0.6030 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 98 | 0.3307 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 147 | 0.3022 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 4.0 | 196 | 0.2354 | 0.3121 | 0.4343 | 0.7171 | 0.3114 |
| No log | 5.0 | 245 | 0.1831 | 0.5306 | 0.6169 | 0.7313 | 0.5335 |
| No log | 6.0 | 294 | 0.1580 | 0.6355 | 0.6895 | 0.7504 | 0.6377 |
| No log | 7.0 | 343 | 0.1408 | 0.6779 | 0.7257 | 0.7702 | 0.6861 |
| No log | 8.0 | 392 | 0.1325 | 0.7228 | 0.7556 | 0.7866 | 0.7270 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1