---
license: apache-2.0
base_model: judy93536/distilroberta-rbm231k-ep20-op40
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta-rbm231k-ep20-op40-phr2
  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-rbm231k-ep20-op40-phr2

This model is a fine-tuned version of [judy93536/distilroberta-rbm231k-ep20-op40](https://huggingface.co/judy93536/distilroberta-rbm231k-ep20-op40) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1783
- Accuracy: 0.9590

## 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: 1.153335054745316e-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: 0.4
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 250  | 1.0615          | 0.6236   |
| 1.0609        | 2.0   | 500  | 1.0082          | 0.6136   |
| 1.0609        | 3.0   | 750  | 0.9017          | 0.6136   |
| 0.9424        | 4.0   | 1000 | 0.8311          | 0.6136   |
| 0.9424        | 5.0   | 1250 | 0.7762          | 0.6136   |
| 0.807         | 6.0   | 1500 | 0.7233          | 0.6837   |
| 0.807         | 7.0   | 1750 | 0.6546          | 0.7217   |
| 0.676         | 8.0   | 2000 | 0.5831          | 0.7508   |
| 0.676         | 9.0   | 2250 | 0.5061          | 0.7848   |
| 0.5141        | 10.0  | 2500 | 0.4108          | 0.8509   |
| 0.5141        | 11.0  | 2750 | 0.2958          | 0.9019   |
| 0.3067        | 12.0  | 3000 | 0.2108          | 0.9309   |
| 0.3067        | 13.0  | 3250 | 0.2005          | 0.9339   |
| 0.1739        | 14.0  | 3500 | 0.1710          | 0.9409   |
| 0.1739        | 15.0  | 3750 | 0.1635          | 0.9459   |
| 0.1312        | 16.0  | 4000 | 0.1603          | 0.9510   |
| 0.1312        | 17.0  | 4250 | 0.1713          | 0.9489   |
| 0.1123        | 18.0  | 4500 | 0.1696          | 0.9550   |
| 0.1123        | 19.0  | 4750 | 0.1658          | 0.9550   |
| 0.1021        | 20.0  | 5000 | 0.1716          | 0.9560   |
| 0.1021        | 21.0  | 5250 | 0.1601          | 0.9600   |
| 0.0906        | 22.0  | 5500 | 0.1622          | 0.9590   |
| 0.0906        | 23.0  | 5750 | 0.1742          | 0.9600   |
| 0.0856        | 24.0  | 6000 | 0.1672          | 0.9600   |
| 0.0856        | 25.0  | 6250 | 0.1773          | 0.9580   |
| 0.0814        | 26.0  | 6500 | 0.1723          | 0.9610   |
| 0.0814        | 27.0  | 6750 | 0.1766          | 0.9570   |
| 0.077         | 28.0  | 7000 | 0.1793          | 0.9560   |
| 0.077         | 29.0  | 7250 | 0.1782          | 0.9590   |
| 0.0786        | 30.0  | 7500 | 0.1783          | 0.9590   |


### Framework versions

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