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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: group1_non_all_zero
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. -->
# group1_non_all_zero
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7437
- Precision: 0.0149
- Recall: 0.1076
- F1: 0.0262
- Accuracy: 0.9260
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 15 | 1.0746 | 0.0007 | 0.0633 | 0.0013 | 0.4145 |
| No log | 2.0 | 30 | 0.8623 | 0.0023 | 0.1139 | 0.0045 | 0.6250 |
| No log | 3.0 | 45 | 0.7242 | 0.0024 | 0.0696 | 0.0046 | 0.7334 |
| No log | 4.0 | 60 | 0.6181 | 0.0037 | 0.0696 | 0.0070 | 0.8030 |
| No log | 5.0 | 75 | 0.6489 | 0.0090 | 0.1329 | 0.0169 | 0.8282 |
| No log | 6.0 | 90 | 0.6538 | 0.0091 | 0.1266 | 0.0170 | 0.8445 |
| No log | 7.0 | 105 | 0.6189 | 0.0103 | 0.1013 | 0.0188 | 0.8893 |
| No log | 8.0 | 120 | 0.6328 | 0.0101 | 0.1013 | 0.0183 | 0.8917 |
| No log | 9.0 | 135 | 0.6561 | 0.0119 | 0.1076 | 0.0215 | 0.9099 |
| No log | 10.0 | 150 | 0.6537 | 0.0152 | 0.1139 | 0.0267 | 0.9265 |
| No log | 11.0 | 165 | 0.6939 | 0.0182 | 0.1139 | 0.0314 | 0.9385 |
| No log | 12.0 | 180 | 0.7481 | 0.0113 | 0.0949 | 0.0203 | 0.9103 |
| No log | 13.0 | 195 | 0.7242 | 0.0150 | 0.1203 | 0.0267 | 0.9209 |
| No log | 14.0 | 210 | 0.7553 | 0.0140 | 0.1013 | 0.0247 | 0.9229 |
| No log | 15.0 | 225 | 0.7437 | 0.0149 | 0.1076 | 0.0262 | 0.9260 |
### Framework versions
- Transformers 4.30.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3
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