---
license: mit
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model-index:
- name: deberta_amazon_reviews_v1
  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: 0.6184
---

<!-- 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_amazon_reviews_v1

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: 0.9076
- Accuracy: 0.6184

## 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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9312        | 0.2   | 5000  | 0.9796          | 0.5856   |
| 0.9316        | 0.4   | 10000 | 0.9336          | 0.5974   |
| 0.9076        | 0.6   | 15000 | 0.9171          | 0.6026   |
| 0.9024        | 0.8   | 20000 | 0.9194          | 0.6046   |
| 0.8794        | 1.0   | 25000 | 0.9109          | 0.6084   |
| 0.8067        | 1.2   | 30000 | 0.9339          | 0.6092   |
| 0.8268        | 1.4   | 35000 | 0.9073          | 0.6162   |
| 0.8205        | 1.6   | 40000 | 0.9042          | 0.6158   |
| 0.795         | 1.8   | 45000 | 0.9189          | 0.6168   |
| 0.7836        | 2.0   | 50000 | 0.9076          | 0.6184   |


### Framework versions

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