---
library_name: transformers
license: mit
base_model: mhr2004/roberta-large-nsp-1000000-1e-06-32
tags:
- generated_from_trainer
model-index:
- name: roberta-large-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
should probably proofread and complete it, then remove this comment. -->

# roberta-large-nsp-1000000-1e-06-32-negcommonsensebalanced-1e-06-64

This model is a fine-tuned version of [mhr2004/roberta-large-nsp-1000000-1e-06-32](https://huggingface.co/mhr2004/roberta-large-nsp-1000000-1e-06-32) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3364

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5348        | 1.0   | 795   | 0.4701          |
| 0.4543        | 2.0   | 1590  | 0.4139          |
| 0.4173        | 3.0   | 2385  | 0.3899          |
| 0.3926        | 4.0   | 3180  | 0.3784          |
| 0.3702        | 5.0   | 3975  | 0.3663          |
| 0.3578        | 6.0   | 4770  | 0.3554          |
| 0.3472        | 7.0   | 5565  | 0.3466          |
| 0.3334        | 8.0   | 6360  | 0.3467          |
| 0.3206        | 9.0   | 7155  | 0.3425          |
| 0.3114        | 10.0  | 7950  | 0.3408          |
| 0.3033        | 11.0  | 8745  | 0.3340          |
| 0.2948        | 12.0  | 9540  | 0.3339          |
| 0.2858        | 13.0  | 10335 | 0.3385          |
| 0.2829        | 14.0  | 11130 | 0.3333          |
| 0.2775        | 15.0  | 11925 | 0.3334          |
| 0.2652        | 16.0  | 12720 | 0.3367          |
| 0.2645        | 17.0  | 13515 | 0.3364          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0