---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
model-index:
- name: roberta-large-nsp-1000-1e-06-8
  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-1000-1e-06-8

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5884

## 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: 32
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 32   | 0.6935          |
| No log        | 2.0   | 64   | 0.6888          |
| No log        | 3.0   | 96   | 0.6834          |
| No log        | 4.0   | 128  | 0.6600          |
| No log        | 5.0   | 160  | 0.6272          |
| No log        | 6.0   | 192  | 0.6098          |
| 0.6812        | 7.0   | 224  | 0.5968          |
| 0.6812        | 8.0   | 256  | 0.5925          |
| 0.6812        | 9.0   | 288  | 0.5899          |
| 0.6812        | 10.0  | 320  | 0.5873          |
| 0.6812        | 11.0  | 352  | 0.5866          |
| 0.6812        | 12.0  | 384  | 0.5870          |
| 0.6056        | 13.0  | 416  | 0.5884          |
| 0.6056        | 14.0  | 448  | 0.5889          |
| 0.6056        | 15.0  | 480  | 0.5887          |
| 0.6056        | 16.0  | 512  | 0.5884          |


### Framework versions

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