---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: micro_base_help_tapt_pretrain_model
  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. -->

# micro_base_help_tapt_pretrain_model

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: 1.5916

## 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: 0.0001
- train_batch_size: 21
- eval_batch_size: 21
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9109        | 0.99  | 40   | 1.6849          |
| 1.7421        | 2.0   | 81   | 1.6620          |
| 1.7411        | 2.99  | 121  | 1.6333          |
| 1.6441        | 4.0   | 162  | 1.6306          |
| 1.6337        | 4.99  | 202  | 1.6137          |
| 1.5774        | 6.0   | 243  | 1.6343          |
| 1.5997        | 6.99  | 283  | 1.5931          |
| 1.5196        | 8.0   | 324  | 1.6018          |
| 1.5416        | 8.99  | 364  | 1.5994          |
| 1.4819        | 10.0  | 405  | 1.5886          |
| 1.5079        | 10.99 | 445  | 1.5938          |
| 1.455         | 12.0  | 486  | 1.5699          |
| 1.4718        | 12.99 | 526  | 1.5947          |
| 1.4157        | 14.0  | 567  | 1.5920          |
| 1.4369        | 14.99 | 607  | 1.5879          |
| 1.3733        | 16.0  | 648  | 1.5745          |
| 1.4017        | 16.99 | 688  | 1.6000          |
| 1.3601        | 18.0  | 729  | 1.5830          |
| 1.3602        | 18.99 | 769  | 1.5846          |
| 1.3152        | 20.0  | 810  | 1.5940          |
| 1.3437        | 20.99 | 850  | 1.5942          |
| 1.2904        | 22.0  | 891  | 1.5787          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2