peft safetensors generated_from_trainer base_model:roberta-large license:mit region:us
---
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: roberta-large
model-index:
- name: p-tuning-roberta-large-with-mrpc
  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. -->

# p-tuning-roberta-large-with-mrpc

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: 0.5925
- Accuracy: 0.6957
- F1: 0.7992

## 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: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 58   | 0.6199          | 0.6754   | 0.8003 |
| No log        | 2.0   | 116  | 0.6082          | 0.6939   | 0.8066 |
| No log        | 3.0   | 174  | 0.6217          | 0.6725   | 0.8013 |
| No log        | 4.0   | 232  | 0.6317          | 0.6667   | 0.7993 |
| No log        | 5.0   | 290  | 0.6402          | 0.6499   | 0.7703 |
| No log        | 6.0   | 348  | 0.6219          | 0.6678   | 0.7994 |
| No log        | 7.0   | 406  | 0.6287          | 0.6684   | 0.7556 |
| No log        | 8.0   | 464  | 0.5914          | 0.6991   | 0.8051 |
| 0.6347        | 9.0   | 522  | 0.5826          | 0.6875   | 0.8022 |
| 0.6347        | 10.0  | 580  | 0.6129          | 0.6875   | 0.7764 |
| 0.6347        | 11.0  | 638  | 0.5942          | 0.6922   | 0.8036 |
| 0.6347        | 12.0  | 696  | 0.5975          | 0.6887   | 0.7822 |
| 0.6347        | 13.0  | 754  | 0.5943          | 0.6899   | 0.7963 |
| 0.6347        | 14.0  | 812  | 0.5863          | 0.6968   | 0.8039 |
| 0.6347        | 15.0  | 870  | 0.5880          | 0.6945   | 0.7998 |
| 0.6347        | 16.0  | 928  | 0.5967          | 0.6858   | 0.7982 |
| 0.6347        | 17.0  | 986  | 0.5951          | 0.6968   | 0.8020 |
| 0.5717        | 18.0  | 1044 | 0.5931          | 0.7043   | 0.7981 |
| 0.5717        | 19.0  | 1102 | 0.5936          | 0.6974   | 0.8006 |
| 0.5717        | 20.0  | 1160 | 0.5925          | 0.6957   | 0.7992 |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0