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---
tags:
- generated_from_trainer
model-index:
- name: CoVBERT
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. -->
# CoVBERT
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1343
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3432 | 0.02 | 100 | 1.4642 |
| 1.4307 | 0.04 | 200 | 1.2907 |
| 1.3923 | 0.06 | 300 | 1.2445 |
| 1.2719 | 0.08 | 400 | 1.1913 |
| 1.1292 | 0.1 | 500 | 0.9962 |
| 0.9344 | 0.12 | 600 | 0.7351 |
| 0.7481 | 0.14 | 700 | 0.6377 |
| 0.6194 | 0.16 | 800 | 0.4843 |
| 0.4363 | 0.18 | 900 | 0.4043 |
| 0.416 | 0.2 | 1000 | 0.3693 |
| 0.3295 | 0.22 | 1100 | 0.3520 |
| 0.3416 | 0.24 | 1200 | 0.3343 |
| 0.3755 | 0.26 | 1300 | 0.3274 |
| 0.3064 | 0.28 | 1400 | 0.3127 |
| 0.3295 | 0.3 | 1500 | 0.2998 |
| 0.2928 | 0.32 | 1600 | 0.2965 |
| 0.3069 | 0.34 | 1700 | 0.2877 |
| 0.3048 | 0.36 | 1800 | 0.2850 |
| 0.2916 | 0.38 | 1900 | 0.2817 |
| 0.2979 | 0.4 | 2000 | 0.2591 |
| 0.2846 | 0.42 | 2100 | 0.2540 |
| 0.2568 | 0.44 | 2200 | 0.3389 |
| 0.277 | 0.46 | 2300 | 0.2369 |
| 0.2385 | 0.48 | 2400 | 0.2238 |
| 0.2477 | 0.5 | 2500 | 0.2160 |
| 0.2271 | 0.52 | 2600 | 0.2139 |
| 0.2457 | 0.54 | 2700 | 0.2024 |
| 0.2037 | 0.56 | 2800 | 0.2085 |
| 0.1865 | 0.58 | 2900 | 0.1978 |
| 0.2354 | 0.6 | 3000 | 0.1929 |
| 0.2001 | 0.62 | 3100 | 0.1865 |
| 0.2396 | 0.64 | 3200 | 0.1832 |
| 0.2197 | 0.66 | 3300 | 0.1790 |
| 0.1813 | 0.68 | 3400 | 0.1767 |
| 0.2109 | 0.7 | 3500 | 0.1970 |
| 0.1956 | 0.72 | 3600 | 0.1658 |
| 0.182 | 0.74 | 3700 | 0.1629 |
| 0.1916 | 0.76 | 3800 | 0.1610 |
| 0.1777 | 0.78 | 3900 | 0.1557 |
| 0.2005 | 0.8 | 4000 | 0.1492 |
| 0.1553 | 0.82 | 4100 | 0.1530 |
| 0.1631 | 0.84 | 4200 | 0.1448 |
| 0.1591 | 0.86 | 4300 | 0.1445 |
| 0.1499 | 0.88 | 4400 | 0.1427 |
| 0.1487 | 0.9 | 4500 | 0.1418 |
| 0.1638 | 0.92 | 4600 | 0.1381 |
| 0.1745 | 0.94 | 4700 | 0.1390 |
| 0.1551 | 0.96 | 4800 | 0.1366 |
| 0.1408 | 0.98 | 4900 | 0.1324 |
| 0.1254 | 1.0 | 5000 | 0.1356 |
### Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu113
- Tokenizers 0.12.1
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