---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: best_model-yelp_polarity-64-100
  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. -->

# best_model-yelp_polarity-64-100

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co./albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7418
- Accuracy: 0.9219

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 150

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 0.8689          | 0.9062   |
| No log        | 2.0   | 8    | 0.8610          | 0.9062   |
| 0.4308        | 3.0   | 12   | 0.8208          | 0.9062   |
| 0.4308        | 4.0   | 16   | 0.7905          | 0.9141   |
| 0.34          | 5.0   | 20   | 0.7690          | 0.9141   |
| 0.34          | 6.0   | 24   | 0.7703          | 0.9141   |
| 0.34          | 7.0   | 28   | 0.7918          | 0.9141   |
| 0.2192        | 8.0   | 32   | 0.7998          | 0.9062   |
| 0.2192        | 9.0   | 36   | 0.8100          | 0.9062   |
| 0.1324        | 10.0  | 40   | 0.8201          | 0.9062   |
| 0.1324        | 11.0  | 44   | 0.8098          | 0.9062   |
| 0.1324        | 12.0  | 48   | 0.7964          | 0.9062   |
| 0.0915        | 13.0  | 52   | 0.7568          | 0.9062   |
| 0.0915        | 14.0  | 56   | 0.7334          | 0.9062   |
| 0.0043        | 15.0  | 60   | 0.6802          | 0.9062   |
| 0.0043        | 16.0  | 64   | 0.6424          | 0.9141   |
| 0.0043        | 17.0  | 68   | 0.6256          | 0.9141   |
| 0.0           | 18.0  | 72   | 0.6206          | 0.9141   |
| 0.0           | 19.0  | 76   | 0.6239          | 0.9141   |
| 0.0           | 20.0  | 80   | 0.6272          | 0.9141   |
| 0.0           | 21.0  | 84   | 0.6317          | 0.9141   |
| 0.0           | 22.0  | 88   | 0.6363          | 0.9141   |
| 0.0           | 23.0  | 92   | 0.6404          | 0.9141   |
| 0.0           | 24.0  | 96   | 0.6448          | 0.9141   |
| 0.0           | 25.0  | 100  | 0.6481          | 0.9062   |
| 0.0           | 26.0  | 104  | 0.6504          | 0.9062   |
| 0.0           | 27.0  | 108  | 0.6511          | 0.9062   |
| 0.0           | 28.0  | 112  | 0.6515          | 0.9062   |
| 0.0           | 29.0  | 116  | 0.6518          | 0.9141   |
| 0.0           | 30.0  | 120  | 0.6518          | 0.9141   |
| 0.0           | 31.0  | 124  | 0.6517          | 0.9141   |
| 0.0           | 32.0  | 128  | 0.6517          | 0.9141   |
| 0.0           | 33.0  | 132  | 0.6518          | 0.9141   |
| 0.0           | 34.0  | 136  | 0.6524          | 0.9141   |
| 0.0           | 35.0  | 140  | 0.6528          | 0.9141   |
| 0.0           | 36.0  | 144  | 0.6535          | 0.9141   |
| 0.0           | 37.0  | 148  | 0.6540          | 0.9141   |
| 0.0           | 38.0  | 152  | 0.6545          | 0.9141   |
| 0.0           | 39.0  | 156  | 0.6553          | 0.9141   |
| 0.0           | 40.0  | 160  | 0.6558          | 0.9141   |
| 0.0           | 41.0  | 164  | 0.6566          | 0.9141   |
| 0.0           | 42.0  | 168  | 0.6574          | 0.9141   |
| 0.0           | 43.0  | 172  | 0.6584          | 0.9141   |
| 0.0           | 44.0  | 176  | 0.6596          | 0.9141   |
| 0.0           | 45.0  | 180  | 0.6605          | 0.9141   |
| 0.0           | 46.0  | 184  | 0.6616          | 0.9141   |
| 0.0           | 47.0  | 188  | 0.6626          | 0.9141   |
| 0.0           | 48.0  | 192  | 0.6633          | 0.9141   |
| 0.0           | 49.0  | 196  | 0.6642          | 0.9219   |
| 0.0           | 50.0  | 200  | 0.6649          | 0.9219   |
| 0.0           | 51.0  | 204  | 0.6660          | 0.9219   |
| 0.0           | 52.0  | 208  | 0.6670          | 0.9219   |
| 0.0           | 53.0  | 212  | 0.6679          | 0.9219   |
| 0.0           | 54.0  | 216  | 0.6688          | 0.9219   |
| 0.0           | 55.0  | 220  | 0.6694          | 0.9219   |
| 0.0           | 56.0  | 224  | 0.6701          | 0.9219   |
| 0.0           | 57.0  | 228  | 0.6710          | 0.9219   |
| 0.0           | 58.0  | 232  | 0.6718          | 0.9219   |
| 0.0           | 59.0  | 236  | 0.6723          | 0.9219   |
| 0.0           | 60.0  | 240  | 0.6733          | 0.9219   |
| 0.0           | 61.0  | 244  | 0.6741          | 0.9219   |
| 0.0           | 62.0  | 248  | 0.6749          | 0.9219   |
| 0.0           | 63.0  | 252  | 0.6759          | 0.9219   |
| 0.0           | 64.0  | 256  | 0.6766          | 0.9219   |
| 0.0           | 65.0  | 260  | 0.6773          | 0.9219   |
| 0.0           | 66.0  | 264  | 0.6783          | 0.9219   |
| 0.0           | 67.0  | 268  | 0.6791          | 0.9219   |
| 0.0           | 68.0  | 272  | 0.6803          | 0.9219   |
| 0.0           | 69.0  | 276  | 0.6813          | 0.9219   |
| 0.0           | 70.0  | 280  | 0.6824          | 0.9219   |
| 0.0           | 71.0  | 284  | 0.6831          | 0.9219   |
| 0.0           | 72.0  | 288  | 0.6839          | 0.9219   |
| 0.0           | 73.0  | 292  | 0.6850          | 0.9219   |
| 0.0           | 74.0  | 296  | 0.6860          | 0.9219   |
| 0.0           | 75.0  | 300  | 0.6866          | 0.9219   |
| 0.0           | 76.0  | 304  | 0.6874          | 0.9219   |
| 0.0           | 77.0  | 308  | 0.6883          | 0.9219   |
| 0.0           | 78.0  | 312  | 0.6892          | 0.9219   |
| 0.0           | 79.0  | 316  | 0.6901          | 0.9219   |
| 0.0           | 80.0  | 320  | 0.6910          | 0.9219   |
| 0.0           | 81.0  | 324  | 0.6919          | 0.9219   |
| 0.0           | 82.0  | 328  | 0.6929          | 0.9219   |
| 0.0           | 83.0  | 332  | 0.6937          | 0.9219   |
| 0.0           | 84.0  | 336  | 0.6948          | 0.9219   |
| 0.0           | 85.0  | 340  | 0.6957          | 0.9219   |
| 0.0           | 86.0  | 344  | 0.6968          | 0.9219   |
| 0.0           | 87.0  | 348  | 0.6978          | 0.9219   |
| 0.0           | 88.0  | 352  | 0.6988          | 0.9219   |
| 0.0           | 89.0  | 356  | 0.6999          | 0.9219   |
| 0.0           | 90.0  | 360  | 0.7008          | 0.9219   |
| 0.0           | 91.0  | 364  | 0.7015          | 0.9219   |
| 0.0           | 92.0  | 368  | 0.7021          | 0.9219   |
| 0.0           | 93.0  | 372  | 0.7030          | 0.9219   |
| 0.0           | 94.0  | 376  | 0.7037          | 0.9219   |
| 0.0           | 95.0  | 380  | 0.7046          | 0.9219   |
| 0.0           | 96.0  | 384  | 0.7054          | 0.9219   |
| 0.0           | 97.0  | 388  | 0.7063          | 0.9219   |
| 0.0           | 98.0  | 392  | 0.7069          | 0.9219   |
| 0.0           | 99.0  | 396  | 0.7080          | 0.9219   |
| 0.0           | 100.0 | 400  | 0.7089          | 0.9219   |
| 0.0           | 101.0 | 404  | 0.7098          | 0.9219   |
| 0.0           | 102.0 | 408  | 0.7107          | 0.9219   |
| 0.0           | 103.0 | 412  | 0.7118          | 0.9219   |
| 0.0           | 104.0 | 416  | 0.7131          | 0.9219   |
| 0.0           | 105.0 | 420  | 0.7140          | 0.9219   |
| 0.0           | 106.0 | 424  | 0.7149          | 0.9219   |
| 0.0           | 107.0 | 428  | 0.7161          | 0.9219   |
| 0.0           | 108.0 | 432  | 0.7174          | 0.9219   |
| 0.0           | 109.0 | 436  | 0.7183          | 0.9219   |
| 0.0           | 110.0 | 440  | 0.7193          | 0.9219   |
| 0.0           | 111.0 | 444  | 0.7203          | 0.9219   |
| 0.0           | 112.0 | 448  | 0.7210          | 0.9219   |
| 0.0           | 113.0 | 452  | 0.7217          | 0.9219   |
| 0.0           | 114.0 | 456  | 0.7226          | 0.9219   |
| 0.0           | 115.0 | 460  | 0.7231          | 0.9219   |
| 0.0           | 116.0 | 464  | 0.7237          | 0.9219   |
| 0.0           | 117.0 | 468  | 0.7245          | 0.9219   |
| 0.0           | 118.0 | 472  | 0.7253          | 0.9219   |
| 0.0           | 119.0 | 476  | 0.7259          | 0.9219   |
| 0.0           | 120.0 | 480  | 0.7269          | 0.9219   |
| 0.0           | 121.0 | 484  | 0.7279          | 0.9219   |
| 0.0           | 122.0 | 488  | 0.7289          | 0.9219   |
| 0.0           | 123.0 | 492  | 0.7297          | 0.9219   |
| 0.0           | 124.0 | 496  | 0.7308          | 0.9219   |
| 0.0           | 125.0 | 500  | 0.7315          | 0.9219   |
| 0.0           | 126.0 | 504  | 0.7324          | 0.9219   |
| 0.0           | 127.0 | 508  | 0.7330          | 0.9219   |
| 0.0           | 128.0 | 512  | 0.7336          | 0.9219   |
| 0.0           | 129.0 | 516  | 0.7344          | 0.9219   |
| 0.0           | 130.0 | 520  | 0.7352          | 0.9219   |
| 0.0           | 131.0 | 524  | 0.7361          | 0.9219   |
| 0.0           | 132.0 | 528  | 0.7366          | 0.9219   |
| 0.0           | 133.0 | 532  | 0.7373          | 0.9219   |
| 0.0           | 134.0 | 536  | 0.7380          | 0.9219   |
| 0.0           | 135.0 | 540  | 0.7385          | 0.9219   |
| 0.0           | 136.0 | 544  | 0.7390          | 0.9219   |
| 0.0           | 137.0 | 548  | 0.7394          | 0.9219   |
| 0.0           | 138.0 | 552  | 0.7399          | 0.9219   |
| 0.0           | 139.0 | 556  | 0.7402          | 0.9219   |
| 0.0           | 140.0 | 560  | 0.7405          | 0.9219   |
| 0.0           | 141.0 | 564  | 0.7408          | 0.9219   |
| 0.0           | 142.0 | 568  | 0.7410          | 0.9219   |
| 0.0           | 143.0 | 572  | 0.7412          | 0.9219   |
| 0.0           | 144.0 | 576  | 0.7414          | 0.9219   |
| 0.0           | 145.0 | 580  | 0.7415          | 0.9219   |
| 0.0           | 146.0 | 584  | 0.7417          | 0.9219   |
| 0.0           | 147.0 | 588  | 0.7417          | 0.9219   |
| 0.0           | 148.0 | 592  | 0.7418          | 0.9219   |
| 0.0           | 149.0 | 596  | 0.7418          | 0.9219   |
| 0.0           | 150.0 | 600  | 0.7418          | 0.9219   |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3