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---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: output
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# output
This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0014
- F1: 0.9009
- Accuracy: 0.89
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 0.3529 | 0.16 | 10 | 0.2584 | 0.6667 | 0.5 |
| 0.2348 | 0.32 | 20 | 0.0989 | 0.6667 | 0.5 |
| 0.0492 | 0.48 | 30 | 0.0314 | 0.9615 | 0.96 |
| 0.0336 | 0.64 | 40 | 0.0132 | 0.6849 | 0.54 |
| 0.0185 | 0.8 | 50 | 0.0345 | 0.6667 | 0.5 |
| 0.0114 | 0.96 | 60 | 0.0490 | 0.9524 | 0.95 |
| 0.0118 | 1.12 | 70 | 0.0235 | 0.7042 | 0.58 |
| 0.01 | 1.28 | 80 | 0.0352 | 0.7299 | 0.63 |
| 0.0061 | 1.44 | 90 | 0.0195 | 0.8 | 0.75 |
| 0.0067 | 1.6 | 100 | 0.0108 | 0.8547 | 0.83 |
| 0.0055 | 1.76 | 110 | 0.0186 | 0.7874 | 0.73 |
| 0.0052 | 1.92 | 120 | 0.0141 | 0.9174 | 0.91 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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