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mhr2004/roberta-base-nsp-1000000-1e-06-32-negcommonsensebalanced-1e-06-64
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---
library_name: transformers
license: mit
base_model: mhr2004/roberta-base-nsp-1000000-1e-06-32
tags:
- generated_from_trainer
model-index:
- name: roberta-base-nsp-1000000-1e-06-32-negcommonsensebalanced-1e-06-64
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-base-nsp-1000000-1e-06-32-negcommonsensebalanced-1e-06-64
This model is a fine-tuned version of [mhr2004/roberta-base-nsp-1000000-1e-06-32](https://huggingface.co/mhr2004/roberta-base-nsp-1000000-1e-06-32) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4028
## 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: 1e-06
- train_batch_size: 256
- eval_batch_size: 1024
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5812 | 1.0 | 795 | 0.5384 |
| 0.5273 | 2.0 | 1590 | 0.5009 |
| 0.5051 | 3.0 | 2385 | 0.4822 |
| 0.4865 | 4.0 | 3180 | 0.4731 |
| 0.4723 | 5.0 | 3975 | 0.4582 |
| 0.4616 | 6.0 | 4770 | 0.4602 |
| 0.4526 | 7.0 | 5565 | 0.4426 |
| 0.44 | 8.0 | 6360 | 0.4402 |
| 0.4329 | 9.0 | 7155 | 0.4316 |
| 0.4288 | 10.0 | 7950 | 0.4282 |
| 0.4174 | 11.0 | 8745 | 0.4234 |
| 0.4134 | 12.0 | 9540 | 0.4205 |
| 0.4101 | 13.0 | 10335 | 0.4203 |
| 0.4076 | 14.0 | 11130 | 0.4152 |
| 0.4028 | 15.0 | 11925 | 0.4094 |
| 0.3963 | 16.0 | 12720 | 0.4103 |
| 0.393 | 17.0 | 13515 | 0.4088 |
| 0.3899 | 18.0 | 14310 | 0.4120 |
| 0.3897 | 19.0 | 15105 | 0.4050 |
| 0.3842 | 20.0 | 15900 | 0.4051 |
| 0.3839 | 21.0 | 16695 | 0.4050 |
| 0.3791 | 22.0 | 17490 | 0.4015 |
| 0.3801 | 23.0 | 18285 | 0.4035 |
| 0.3807 | 24.0 | 19080 | 0.4016 |
| 0.3738 | 25.0 | 19875 | 0.4028 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0