---
license: apache-2.0
base_model: judy93536/distilroberta-base-ep20
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta-base-ep20-phrase5k
  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. -->

# distilroberta-base-ep20-phrase5k

This model is a fine-tuned version of [judy93536/distilroberta-base-ep20](https://huggingface.co/judy93536/distilroberta-base-ep20) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1361
- Accuracy: 0.9540

## 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: 1.123335054745316e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.28
- num_epochs: 13
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 250  | 1.0595          | 0.6046   |
| 1.0445        | 2.0   | 500  | 0.8412          | 0.6136   |
| 1.0445        | 3.0   | 750  | 0.6597          | 0.7197   |
| 0.6876        | 4.0   | 1000 | 0.5043          | 0.7768   |
| 0.6876        | 5.0   | 1250 | 0.3559          | 0.8709   |
| 0.3881        | 6.0   | 1500 | 0.2273          | 0.9289   |
| 0.3881        | 7.0   | 1750 | 0.1852          | 0.9369   |
| 0.1977        | 8.0   | 2000 | 0.1567          | 0.9449   |
| 0.1977        | 9.0   | 2250 | 0.1396          | 0.9510   |
| 0.1436        | 10.0  | 2500 | 0.1493          | 0.9489   |
| 0.1436        | 11.0  | 2750 | 0.1397          | 0.9499   |
| 0.123         | 12.0  | 3000 | 0.1334          | 0.9530   |
| 0.123         | 13.0  | 3250 | 0.1361          | 0.9540   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0