---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: HBERTv1_emb_compress_48_L12_H256_A4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# HBERTv1_emb_compress_48_L12_H256_A4

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.0468
- Accuracy: 0.1510

## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 7.1159        | 0.11  | 10000  | 7.0948          | 0.0805   |
| 6.698         | 0.22  | 20000  | 6.6913          | 0.1060   |
| 6.5481        | 0.33  | 30000  | 6.5473          | 0.1167   |
| 6.4589        | 0.44  | 40000  | 6.4576          | 0.1252   |
| 6.3925        | 0.55  | 50000  | 6.3858          | 0.1306   |
| 6.3433        | 0.66  | 60000  | 6.3356          | 0.1353   |
| 6.2983        | 0.76  | 70000  | 6.2965          | 0.1376   |
| 6.268         | 0.87  | 80000  | 6.2643          | 0.1397   |
| 6.2359        | 0.98  | 90000  | 6.2381          | 0.1411   |
| 6.2186        | 1.09  | 100000 | 6.2160          | 0.1429   |
| 6.1915        | 1.2   | 110000 | 6.1972          | 0.1439   |
| 6.1811        | 1.31  | 120000 | 6.1834          | 0.1440   |
| 6.1696        | 1.42  | 130000 | 6.1692          | 0.1455   |
| 6.1621        | 1.53  | 140000 | 6.1557          | 0.1454   |
| 6.1417        | 1.64  | 150000 | 6.1466          | 0.1468   |
| 6.1391        | 1.75  | 160000 | 6.1364          | 0.1466   |
| 6.1338        | 1.86  | 170000 | 6.1281          | 0.1476   |
| 6.1285        | 1.97  | 180000 | 6.1200          | 0.1477   |
| 6.1147        | 2.08  | 190000 | 6.1135          | 0.1483   |
| 6.1139        | 2.18  | 200000 | 6.1083          | 0.1486   |
| 6.1004        | 2.29  | 210000 | 6.1004          | 0.1487   |
| 6.0997        | 2.4   | 220000 | 6.0964          | 0.1489   |
| 6.092         | 2.51  | 230000 | 6.0922          | 0.1490   |
| 6.089         | 2.62  | 240000 | 6.0862          | 0.1490   |
| 6.0841        | 2.73  | 250000 | 6.0829          | 0.1498   |
| 6.0847        | 2.84  | 260000 | 6.0799          | 0.1496   |
| 6.0834        | 2.95  | 270000 | 6.0760          | 0.1501   |
| 6.0752        | 3.06  | 280000 | 6.0715          | 0.1502   |
| 6.0693        | 3.17  | 290000 | 6.0697          | 0.1502   |
| 6.0677        | 3.28  | 300000 | 6.0679          | 0.1502   |
| 6.0646        | 3.39  | 310000 | 6.0646          | 0.1503   |
| 6.0625        | 3.5   | 320000 | 6.0623          | 0.1503   |
| 6.0536        | 3.6   | 330000 | 6.0593          | 0.1507   |
| 6.0574        | 3.71  | 340000 | 6.0577          | 0.1507   |
| 6.0496        | 3.82  | 350000 | 6.0560          | 0.1508   |
| 6.0525        | 3.93  | 360000 | 6.0543          | 0.1507   |
| 6.0498        | 4.04  | 370000 | 6.0508          | 0.1509   |
| 6.0557        | 4.15  | 380000 | 6.0509          | 0.1508   |
| 6.0445        | 4.26  | 390000 | 6.0483          | 0.1509   |
| 6.0466        | 4.37  | 400000 | 6.0470          | 0.1510   |
| 6.0507        | 4.48  | 410000 | 6.0471          | 0.1510   |
| 6.0459        | 4.59  | 420000 | 6.0468          | 0.1510   |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.13.3