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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-finetuned-recores
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. -->
# mdeberta-v3-base-finetuned-recores
This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6094
- Accuracy: 0.2011
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6112 | 1.0 | 1047 | 1.6094 | 0.1901 |
| 1.608 | 2.0 | 2094 | 1.6094 | 0.1873 |
| 1.6127 | 3.0 | 3141 | 1.6095 | 0.1983 |
| 1.6125 | 4.0 | 4188 | 1.6094 | 0.2424 |
| 1.6118 | 5.0 | 5235 | 1.6094 | 0.1956 |
| 1.6181 | 6.0 | 6282 | 1.6094 | 0.2094 |
| 1.6229 | 7.0 | 7329 | 1.6095 | 0.1680 |
| 1.6125 | 8.0 | 8376 | 1.6094 | 0.1736 |
| 1.6134 | 9.0 | 9423 | 1.6094 | 0.2066 |
| 1.6174 | 10.0 | 10470 | 1.6093 | 0.2204 |
| 1.6161 | 11.0 | 11517 | 1.6096 | 0.2121 |
| 1.6198 | 12.0 | 12564 | 1.6094 | 0.2039 |
| 1.6182 | 13.0 | 13611 | 1.6094 | 0.2287 |
| 1.6208 | 14.0 | 14658 | 1.6094 | 0.2287 |
| 1.6436 | 15.0 | 15705 | 1.6092 | 0.2287 |
| 1.6209 | 16.0 | 16752 | 1.6094 | 0.2094 |
| 1.6097 | 17.0 | 17799 | 1.6094 | 0.2094 |
| 1.6115 | 18.0 | 18846 | 1.6094 | 0.2149 |
| 1.6249 | 19.0 | 19893 | 1.6094 | 0.1956 |
| 1.6201 | 20.0 | 20940 | 1.6094 | 0.1763 |
| 1.6217 | 21.0 | 21987 | 1.6094 | 0.1956 |
| 1.6193 | 22.0 | 23034 | 1.6094 | 0.1846 |
| 1.6171 | 23.0 | 24081 | 1.6095 | 0.1983 |
| 1.6123 | 24.0 | 25128 | 1.6095 | 0.1846 |
| 1.6164 | 25.0 | 26175 | 1.6094 | 0.2011 |
### Framework versions
- Transformers 4.19.0
- Pytorch 1.10.1+cu102
- Datasets 2.2.1
- Tokenizers 0.12.1
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