---
license: mit
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model-index:
- name: deberta_v3_amazon_reviews
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: amazon_reviews_multi
      type: amazon_reviews_multi
      args: en
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.61
---

<!-- 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. -->

# deberta_v3_amazon_reviews

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9723
- Accuracy: 0.61

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9339        | 0.2   | 5000  | 0.9879          | 0.5876   |
| 0.9386        | 0.4   | 10000 | 0.9408          | 0.5992   |
| 0.9127        | 0.6   | 15000 | 0.9118          | 0.6004   |
| 0.8997        | 0.8   | 20000 | 0.9192          | 0.607    |
| 0.8853        | 1.0   | 25000 | 0.9167          | 0.6018   |
| 0.8159        | 1.2   | 30000 | 0.9364          | 0.6064   |
| 0.8367        | 1.4   | 35000 | 0.9215          | 0.6174   |
| 0.8322        | 1.6   | 40000 | 0.9076          | 0.6108   |
| 0.8142        | 1.8   | 45000 | 0.9305          | 0.6148   |
| 0.8139        | 2.0   | 50000 | 0.9394          | 0.6092   |
| 0.7279        | 2.2   | 55000 | 0.9868          | 0.605    |
| 0.715         | 2.4   | 60000 | 0.9865          | 0.6072   |
| 0.7515        | 2.6   | 65000 | 0.9783          | 0.606    |
| 0.7363        | 2.8   | 70000 | 0.9765          | 0.6096   |
| 0.7405        | 3.0   | 75000 | 0.9723          | 0.61     |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6