---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 1_microsoft_deberta_V1.0
  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. -->

# 1_microsoft_deberta_V1.0

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: 1.0849
- Map@3: 0.7725
- Accuracy: 0.665

## 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: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 25
- total_train_batch_size: 50
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Map@3  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 1.6098        | 0.01  | 10   | 1.6090          | 0.6108 | 0.475    |
| 1.6057        | 0.02  | 20   | 1.6027          | 0.7375 | 0.625    |
| 1.5615        | 0.03  | 30   | 1.4516          | 0.7458 | 0.64     |
| 1.2061        | 0.03  | 40   | 1.2130          | 0.7292 | 0.595    |
| 1.1028        | 0.04  | 50   | 1.0947          | 0.765  | 0.65     |
| 1.0682        | 0.05  | 60   | 1.0849          | 0.7725 | 0.665    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.9.0
- Tokenizers 0.13.3