---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Classifier_30k
  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. -->

# Classifier_30k

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1296
- Accuracy: 0.9876

## 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: 2e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 0.3588        | 0.9994  | 831   | 0.3084          | 0.9091   |
| 0.1252        | 2.0     | 1663  | 0.2260          | 0.9453   |
| 0.1123        | 2.9994  | 2494  | 0.1241          | 0.9604   |
| 0.0896        | 4.0     | 3326  | 0.1372          | 0.9655   |
| 0.0749        | 4.9994  | 4157  | 0.1541          | 0.9708   |
| 0.0743        | 6.0     | 4989  | 0.1127          | 0.9715   |
| 0.0596        | 6.9994  | 5820  | 0.1782          | 0.9672   |
| 0.0494        | 8.0     | 6652  | 0.1352          | 0.9749   |
| 0.0443        | 8.9994  | 7483  | 0.1232          | 0.9681   |
| 0.0405        | 10.0    | 8315  | 0.0756          | 0.9838   |
| 0.0383        | 10.9994 | 9146  | 0.2025          | 0.9600   |
| 0.0361        | 12.0    | 9978  | 0.1130          | 0.9796   |
| 0.0288        | 12.9994 | 10809 | 0.0906          | 0.9855   |
| 0.0249        | 14.0    | 11641 | 0.1122          | 0.9827   |
| 0.0222        | 14.9994 | 12472 | 0.0713          | 0.9862   |
| 0.0239        | 16.0    | 13304 | 0.0552          | 0.9876   |
| 0.0234        | 16.9994 | 14135 | 0.0728          | 0.9864   |
| 0.0258        | 18.0    | 14967 | 0.0558          | 0.9891   |
| 0.0208        | 18.9994 | 15798 | 0.0715          | 0.9879   |
| 0.0199        | 20.0    | 16630 | 0.0753          | 0.9885   |
| 0.0143        | 20.9994 | 17461 | 0.0812          | 0.9872   |
| 0.0255        | 22.0    | 18293 | 0.1661          | 0.9744   |
| 0.0156        | 22.9994 | 19124 | 0.0751          | 0.9883   |
| 0.013         | 24.0    | 19956 | 0.0718          | 0.9862   |
| 0.0126        | 24.9994 | 20787 | 0.0829          | 0.9853   |
| 0.0123        | 26.0    | 21619 | 0.0848          | 0.9857   |
| 0.0109        | 26.9994 | 22450 | 0.0913          | 0.9864   |
| 0.0095        | 28.0    | 23282 | 0.1607          | 0.9774   |
| 0.0096        | 28.9994 | 24113 | 0.0958          | 0.9853   |
| 0.0074        | 30.0    | 24945 | 0.1264          | 0.9857   |
| 0.0091        | 30.9994 | 25776 | 0.1030          | 0.9881   |
| 0.0096        | 32.0    | 26608 | 0.0954          | 0.9879   |
| 0.0074        | 32.9994 | 27439 | 0.1103          | 0.9885   |
| 0.0067        | 34.0    | 28271 | 0.1803          | 0.9791   |
| 0.0044        | 34.9994 | 29102 | 0.1597          | 0.9817   |
| 0.0045        | 36.0    | 29934 | 0.0878          | 0.9894   |
| 0.0034        | 36.9994 | 30765 | 0.1680          | 0.9806   |
| 0.0066        | 38.0    | 31597 | 0.1114          | 0.9870   |
| 0.0041        | 38.9994 | 32428 | 0.0910          | 0.9896   |
| 0.0043        | 40.0    | 33260 | 0.1435          | 0.9840   |
| 0.0037        | 40.9994 | 34091 | 0.1233          | 0.9881   |
| 0.0046        | 42.0    | 34923 | 0.1347          | 0.9864   |
| 0.0029        | 42.9994 | 35754 | 0.1134          | 0.9883   |
| 0.0017        | 44.0    | 36586 | 0.1125          | 0.9879   |
| 0.0025        | 44.9994 | 37417 | 0.1400          | 0.9859   |
| 0.0023        | 46.0    | 38249 | 0.1228          | 0.9879   |
| 0.0017        | 46.9994 | 39080 | 0.1445          | 0.9862   |
| 0.0011        | 48.0    | 39912 | 0.1375          | 0.9876   |
| 0.0013        | 48.9994 | 40743 | 0.1323          | 0.9876   |
| 0.0021        | 49.9699 | 41550 | 0.1296          | 0.9876   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1