transformers pytorch albert text-classification generated_from_trainer dataset:yelp_review_full license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- yelp_review_full
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: YELP_ALBERT_5E
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: yelp_review_full
      type: yelp_review_full
      config: yelp_review_full
      split: train
      args: yelp_review_full
    metrics:
    - type: accuracy
      value: 0.9733333333333334
      name: Accuracy
---

<!-- 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. -->

# YELP_ALBERT_5E

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the yelp_review_full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1394
- Accuracy: 0.9733

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4967        | 0.03  | 50   | 0.1667          | 0.9467   |
| 0.3268        | 0.06  | 100  | 0.2106          | 0.9133   |
| 0.3413        | 0.1   | 150  | 0.2107          | 0.9667   |
| 0.3172        | 0.13  | 200  | 0.1906          | 0.94     |
| 0.2804        | 0.16  | 250  | 0.2588          | 0.9      |
| 0.2604        | 0.19  | 300  | 0.2023          | 0.94     |
| 0.2532        | 0.22  | 350  | 0.1263          | 0.9533   |
| 0.2103        | 0.26  | 400  | 0.1233          | 0.96     |
| 0.212         | 0.29  | 450  | 0.2019          | 0.9267   |
| 0.2669        | 0.32  | 500  | 0.1110          | 0.9667   |
| 0.2187        | 0.35  | 550  | 0.1542          | 0.96     |
| 0.2203        | 0.38  | 600  | 0.0879          | 0.9733   |
| 0.2699        | 0.42  | 650  | 0.0971          | 0.9667   |
| 0.2107        | 0.45  | 700  | 0.0863          | 0.9667   |
| 0.2443        | 0.48  | 750  | 0.0823          | 0.9733   |
| 0.1987        | 0.51  | 800  | 0.1207          | 0.9733   |
| 0.2326        | 0.54  | 850  | 0.1368          | 0.9667   |
| 0.1787        | 0.58  | 900  | 0.1027          | 0.9667   |
| 0.2159        | 0.61  | 950  | 0.2443          | 0.9333   |
| 0.1316        | 0.64  | 1000 | 0.2035          | 0.9467   |
| 0.2416        | 0.67  | 1050 | 0.0882          | 0.9733   |
| 0.2008        | 0.7   | 1100 | 0.1709          | 0.9533   |
| 0.2065        | 0.74  | 1150 | 0.1098          | 0.9667   |
| 0.2391        | 0.77  | 1200 | 0.1055          | 0.9667   |
| 0.1533        | 0.8   | 1250 | 0.1997          | 0.94     |
| 0.2016        | 0.83  | 1300 | 0.0899          | 0.96     |
| 0.2016        | 0.86  | 1350 | 0.0957          | 0.9733   |
| 0.2316        | 0.9   | 1400 | 0.0784          | 0.98     |
| 0.1839        | 0.93  | 1450 | 0.0784          | 0.9733   |
| 0.2121        | 0.96  | 1500 | 0.1150          | 0.9733   |
| 0.1307        | 0.99  | 1550 | 0.0969          | 0.9733   |
| 0.1271        | 1.02  | 1600 | 0.2326          | 0.9467   |
| 0.1736        | 1.06  | 1650 | 0.0979          | 0.9667   |
| 0.1357        | 1.09  | 1700 | 0.0862          | 0.98     |
| 0.1871        | 1.12  | 1750 | 0.1419          | 0.9667   |
| 0.1411        | 1.15  | 1800 | 0.1301          | 0.96     |
| 0.1317        | 1.18  | 1850 | 0.1602          | 0.9533   |
| 0.1432        | 1.22  | 1900 | 0.1885          | 0.9533   |
| 0.1793        | 1.25  | 1950 | 0.0776          | 0.9667   |
| 0.1322        | 1.28  | 2000 | 0.0822          | 0.9733   |
| 0.1416        | 1.31  | 2050 | 0.0920          | 0.9733   |
| 0.1524        | 1.34  | 2100 | 0.0673          | 0.98     |
| 0.1338        | 1.38  | 2150 | 0.0602          | 0.98     |
| 0.152         | 1.41  | 2200 | 0.0916          | 0.98     |
| 0.1192        | 1.44  | 2250 | 0.0559          | 0.98     |
| 0.1471        | 1.47  | 2300 | 0.1096          | 0.9667   |
| 0.1267        | 1.5   | 2350 | 0.0695          | 0.9733   |
| 0.1776        | 1.54  | 2400 | 0.1363          | 0.96     |
| 0.1495        | 1.57  | 2450 | 0.0818          | 0.98     |
| 0.1158        | 1.6   | 2500 | 0.1282          | 0.9667   |
| 0.1772        | 1.63  | 2550 | 0.0682          | 0.9733   |
| 0.1187        | 1.66  | 2600 | 0.1032          | 0.9733   |
| 0.136         | 1.7   | 2650 | 0.1071          | 0.9667   |
| 0.1829        | 1.73  | 2700 | 0.0753          | 0.9667   |
| 0.1147        | 1.76  | 2750 | 0.1071          | 0.9733   |
| 0.1174        | 1.79  | 2800 | 0.1441          | 0.9667   |
| 0.0707        | 1.82  | 2850 | 0.1362          | 0.9667   |
| 0.1372        | 1.86  | 2900 | 0.1861          | 0.9533   |
| 0.2108        | 1.89  | 2950 | 0.0770          | 0.9733   |
| 0.2014        | 1.92  | 3000 | 0.1114          | 0.9667   |
| 0.1373        | 1.95  | 3050 | 0.1244          | 0.9667   |
| 0.1242        | 1.98  | 3100 | 0.1220          | 0.96     |
| 0.1267        | 2.02  | 3150 | 0.1139          | 0.9733   |
| 0.1021        | 2.05  | 3200 | 0.2013          | 0.9533   |
| 0.1091        | 2.08  | 3250 | 0.1027          | 0.9733   |
| 0.0648        | 2.11  | 3300 | 0.1464          | 0.9733   |
| 0.1207        | 2.14  | 3350 | 0.1255          | 0.9733   |
| 0.0833        | 2.18  | 3400 | 0.0708          | 0.98     |
| 0.0796        | 2.21  | 3450 | 0.1608          | 0.96     |
| 0.0624        | 2.24  | 3500 | 0.0827          | 0.98     |
| 0.0518        | 2.27  | 3550 | 0.0602          | 0.98     |
| 0.1242        | 2.3   | 3600 | 0.0752          | 0.9733   |
| 0.0422        | 2.34  | 3650 | 0.1000          | 0.9733   |
| 0.0748        | 2.37  | 3700 | 0.1171          | 0.9667   |
| 0.0839        | 2.4   | 3750 | 0.1341          | 0.9667   |
| 0.1033        | 2.43  | 3800 | 0.0744          | 0.98     |
| 0.0567        | 2.46  | 3850 | 0.0869          | 0.98     |
| 0.0756        | 2.5   | 3900 | 0.0745          | 0.98     |
| 0.0768        | 2.53  | 3950 | 0.0895          | 0.9733   |
| 0.0878        | 2.56  | 4000 | 0.0703          | 0.98     |
| 0.1023        | 2.59  | 4050 | 0.0806          | 0.98     |
| 0.0807        | 2.62  | 4100 | 0.0338          | 0.9867   |
| 0.0868        | 2.66  | 4150 | 0.0892          | 0.9667   |
| 0.0648        | 2.69  | 4200 | 0.1637          | 0.9533   |
| 0.0535        | 2.72  | 4250 | 0.1622          | 0.9667   |
| 0.0675        | 2.75  | 4300 | 0.1354          | 0.9733   |
| 0.1121        | 2.78  | 4350 | 0.1440          | 0.9533   |
| 0.0714        | 2.82  | 4400 | 0.1022          | 0.9467   |
| 0.0786        | 2.85  | 4450 | 0.1110          | 0.9733   |
| 0.0822        | 2.88  | 4500 | 0.1218          | 0.9733   |
| 0.1075        | 2.91  | 4550 | 0.1041          | 0.9733   |
| 0.0783        | 2.94  | 4600 | 0.0992          | 0.9733   |
| 0.1059        | 2.98  | 4650 | 0.1187          | 0.9733   |
| 0.067         | 3.01  | 4700 | 0.0931          | 0.9733   |
| 0.0425        | 3.04  | 4750 | 0.1252          | 0.9733   |
| 0.0539        | 3.07  | 4800 | 0.1152          | 0.9733   |
| 0.0419        | 3.1   | 4850 | 0.1534          | 0.9667   |
| 0.0462        | 3.13  | 4900 | 0.1398          | 0.9733   |
| 0.0435        | 3.17  | 4950 | 0.1168          | 0.98     |
| 0.0144        | 3.2   | 5000 | 0.1489          | 0.9667   |
| 0.0367        | 3.23  | 5050 | 0.1293          | 0.9733   |
| 0.0336        | 3.26  | 5100 | 0.1353          | 0.9733   |
| 0.0246        | 3.29  | 5150 | 0.0958          | 0.98     |
| 0.0181        | 3.33  | 5200 | 0.1294          | 0.9733   |
| 0.0357        | 3.36  | 5250 | 0.1209          | 0.9733   |
| 0.0683        | 3.39  | 5300 | 0.1748          | 0.96     |
| 0.0353        | 3.42  | 5350 | 0.2159          | 0.9533   |
| 0.0415        | 3.45  | 5400 | 0.1723          | 0.96     |
| 0.0336        | 3.49  | 5450 | 0.1031          | 0.98     |
| 0.0475        | 3.52  | 5500 | 0.0959          | 0.98     |
| 0.0393        | 3.55  | 5550 | 0.2163          | 0.96     |
| 0.0337        | 3.58  | 5600 | 0.1097          | 0.9733   |
| 0.0415        | 3.61  | 5650 | 0.1365          | 0.98     |
| 0.035         | 3.65  | 5700 | 0.1175          | 0.98     |
| 0.0448        | 3.68  | 5750 | 0.1543          | 0.9667   |
| 0.0445        | 3.71  | 5800 | 0.2005          | 0.96     |
| 0.0211        | 3.74  | 5850 | 0.1179          | 0.98     |
| 0.0198        | 3.77  | 5900 | 0.1298          | 0.9733   |
| 0.026         | 3.81  | 5950 | 0.2167          | 0.9667   |
| 0.0412        | 3.84  | 6000 | 0.1224          | 0.98     |
| 0.0446        | 3.87  | 6050 | 0.0798          | 0.98     |
| 0.0174        | 3.9   | 6100 | 0.0577          | 0.9933   |
| 0.0535        | 3.93  | 6150 | 0.1482          | 0.9667   |
| 0.0495        | 3.97  | 6200 | 0.0862          | 0.98     |
| 0.0267        | 4.0   | 6250 | 0.1190          | 0.98     |
| 0.0087        | 4.03  | 6300 | 0.0747          | 0.98     |
| 0.0102        | 4.06  | 6350 | 0.0753          | 0.9867   |
| 0.0178        | 4.09  | 6400 | 0.1812          | 0.9667   |
| 0.0088        | 4.13  | 6450 | 0.0817          | 0.98     |
| 0.0144        | 4.16  | 6500 | 0.0805          | 0.98     |
| 0.014         | 4.19  | 6550 | 0.0862          | 0.9867   |
| 0.0002        | 4.22  | 6600 | 0.0894          | 0.98     |
| 0.0112        | 4.25  | 6650 | 0.1004          | 0.9733   |
| 0.0054        | 4.29  | 6700 | 0.0832          | 0.9867   |
| 0.0001        | 4.32  | 6750 | 0.0812          | 0.9867   |
| 0.0202        | 4.35  | 6800 | 0.1828          | 0.9667   |
| 0.009         | 4.38  | 6850 | 0.1114          | 0.98     |
| 0.0001        | 4.41  | 6900 | 0.1295          | 0.98     |
| 0.0077        | 4.45  | 6950 | 0.1610          | 0.9733   |
| 0.0082        | 4.48  | 7000 | 0.1787          | 0.9667   |
| 0.0198        | 4.51  | 7050 | 0.1485          | 0.9733   |
| 0.0017        | 4.54  | 7100 | 0.1774          | 0.9733   |
| 0.0115        | 4.57  | 7150 | 0.1567          | 0.9733   |
| 0.0001        | 4.61  | 7200 | 0.1534          | 0.9733   |
| 0.0247        | 4.64  | 7250 | 0.2020          | 0.9667   |
| 0.0059        | 4.67  | 7300 | 0.1918          | 0.9667   |
| 0.0052        | 4.7   | 7350 | 0.1315          | 0.98     |
| 0.0076        | 4.73  | 7400 | 0.1289          | 0.98     |
| 0.0218        | 4.77  | 7450 | 0.1610          | 0.9733   |
| 0.0077        | 4.8   | 7500 | 0.1355          | 0.98     |
| 0.0096        | 4.83  | 7550 | 0.1378          | 0.9733   |
| 0.008         | 4.86  | 7600 | 0.1568          | 0.9733   |
| 0.0103        | 4.89  | 7650 | 0.1388          | 0.9733   |
| 0.0009        | 4.93  | 7700 | 0.1221          | 0.98     |
| 0.0287        | 4.96  | 7750 | 0.1448          | 0.9733   |
| 0.01          | 4.99  | 7800 | 0.1394          | 0.9733   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
