---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base-nsp-10000-1e-06-16
  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-base-nsp-10000-1e-06-16

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2827

## 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: 64
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 157  | 0.6924          |
| 0.6939        | 2.0   | 314  | 0.6904          |
| 0.6909        | 3.0   | 471  | 0.6734          |
| 0.6456        | 4.0   | 628  | 0.4767          |
| 0.6456        | 5.0   | 785  | 0.3638          |
| 0.4555        | 6.0   | 942  | 0.3189          |
| 0.3506        | 7.0   | 1099 | 0.3019          |
| 0.3029        | 8.0   | 1256 | 0.3013          |
| 0.2722        | 9.0   | 1413 | 0.3003          |
| 0.2722        | 10.0  | 1570 | 0.2986          |
| 0.2582        | 11.0  | 1727 | 0.2850          |
| 0.237         | 12.0  | 1884 | 0.2805          |
| 0.2182        | 13.0  | 2041 | 0.2884          |
| 0.2182        | 14.0  | 2198 | 0.2844          |
| 0.208         | 15.0  | 2355 | 0.2876          |
| 0.2026        | 16.0  | 2512 | 0.2927          |
| 0.1908        | 17.0  | 2669 | 0.2827          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1