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---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: 008-microsoft-deberta-v3-base-finetuned-yahoo-800_200
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. -->
# 008-microsoft-deberta-v3-base-finetuned-yahoo-800_200
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1139
- F1: 0.6463
- Accuracy: 0.65
- Precision: 0.6514
- Recall: 0.65
- System Ram Used: 4.2190
- System Ram Total: 83.4807
- Gpu Ram Allocated: 2.0914
- Gpu Ram Cached: 24.6602
- Gpu Ram Total: 39.5640
- Gpu Utilization: 33
- Disk Space Used: 31.6928
- Disk Space Total: 78.1898
## 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: 2e-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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | System Ram Used | System Ram Total | Gpu Ram Allocated | Gpu Ram Cached | Gpu Ram Total | Gpu Utilization | Disk Space Used | Disk Space Total |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:---------------:|:----------------:|:-----------------:|:--------------:|:-------------:|:---------------:|:---------------:|:----------------:|
| 2.2992 | 0.52 | 13 | 2.3031 | 0.0182 | 0.1 | 0.01 | 0.1 | 3.9340 | 83.4807 | 2.0915 | 24.6484 | 39.5640 | 50 | 24.7853 | 78.1898 |
| 2.3096 | 1.04 | 26 | 2.2984 | 0.0182 | 0.1 | 0.01 | 0.1 | 4.1195 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 43 | 29.6206 | 78.1898 |
| 2.2906 | 1.56 | 39 | 2.2852 | 0.0648 | 0.145 | 0.0525 | 0.145 | 4.2050 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 51 | 29.6206 | 78.1898 |
| 2.2723 | 2.08 | 52 | 2.2198 | 0.1283 | 0.225 | 0.1625 | 0.225 | 4.2165 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 43 | 31.6924 | 78.1898 |
| 2.1387 | 2.6 | 65 | 2.0293 | 0.2580 | 0.335 | 0.2655 | 0.335 | 4.2218 | 83.4807 | 2.0916 | 24.6602 | 39.5640 | 56 | 31.6925 | 78.1898 |
| 1.9534 | 3.12 | 78 | 1.8757 | 0.3730 | 0.4 | 0.4419 | 0.4 | 4.2092 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 41 | 31.6925 | 78.1898 |
| 1.7689 | 3.64 | 91 | 1.7209 | 0.4443 | 0.48 | 0.5198 | 0.48 | 4.2303 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 46 | 31.6925 | 78.1898 |
| 1.6052 | 4.16 | 104 | 1.6318 | 0.5044 | 0.525 | 0.5139 | 0.525 | 4.2297 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 45 | 31.6926 | 78.1898 |
| 1.4606 | 4.68 | 117 | 1.4969 | 0.5539 | 0.575 | 0.5788 | 0.575 | 4.2315 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 47 | 31.6926 | 78.1898 |
| 1.2963 | 5.2 | 130 | 1.3920 | 0.6037 | 0.61 | 0.6063 | 0.61 | 4.2420 | 83.4807 | 2.0916 | 24.6602 | 39.5640 | 43 | 31.6926 | 78.1898 |
| 1.1948 | 5.72 | 143 | 1.3030 | 0.6251 | 0.63 | 0.6292 | 0.63 | 4.2687 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 48 | 31.6926 | 78.1898 |
| 1.0248 | 6.24 | 156 | 1.2568 | 0.6184 | 0.625 | 0.6354 | 0.625 | 4.2596 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 50 | 31.6927 | 78.1898 |
| 0.9509 | 6.76 | 169 | 1.1911 | 0.6448 | 0.65 | 0.6552 | 0.65 | 4.2625 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 44 | 31.6927 | 78.1898 |
| 0.9081 | 7.28 | 182 | 1.1784 | 0.6441 | 0.655 | 0.6450 | 0.655 | 4.1955 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 50 | 31.6927 | 78.1898 |
| 0.7629 | 7.8 | 195 | 1.1354 | 0.6598 | 0.655 | 0.6737 | 0.655 | 4.1868 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 44 | 31.6927 | 78.1898 |
| 0.7348 | 8.32 | 208 | 1.1369 | 0.6430 | 0.65 | 0.6483 | 0.65 | 4.2168 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 43 | 31.6927 | 78.1898 |
| 0.7443 | 8.84 | 221 | 1.1274 | 0.6531 | 0.66 | 0.6576 | 0.66 | 4.2273 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 51 | 31.6927 | 78.1898 |
| 0.5945 | 9.36 | 234 | 1.1228 | 0.6640 | 0.67 | 0.6694 | 0.67 | 4.1791 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 44 | 31.6928 | 78.1898 |
| 0.6885 | 9.88 | 247 | 1.1145 | 0.6463 | 0.65 | 0.6514 | 0.65 | 4.1849 | 83.4807 | 2.0915 | 24.6602 | 39.5640 | 48 | 31.6928 | 78.1898 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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