transformers safetensors deberta-v2 question-answering generated_from_trainer base_model:timpal0l/mdeberta-v3-base-squad2 license:mit endpoints_compatible region:us
---
license: mit
base_model: timpal0l/mdeberta-v3-base-squad2
tags:
- generated_from_trainer
model-index:
- name: uda_qa_deberta
  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. -->

# uda_qa_deberta

This model is a fine-tuned version of [timpal0l/mdeberta-v3-base-squad2](https://huggingface.co/timpal0l/mdeberta-v3-base-squad2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9272

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7868        | 1.0   | 24   | 1.3981          |
| 0.7556        | 2.0   | 48   | 1.0414          |
| 0.508         | 3.0   | 72   | 0.9954          |
| 0.3307        | 4.0   | 96   | 0.9373          |
| 0.3098        | 5.0   | 120  | 0.9613          |
| 0.2105        | 6.0   | 144  | 0.9799          |
| 0.1567        | 7.0   | 168  | 0.8763          |
| 0.105         | 8.0   | 192  | 0.9742          |
| 0.0942        | 9.0   | 216  | 0.9634          |
| 0.0733        | 10.0  | 240  | 0.9067          |
| 0.0493        | 11.0  | 264  | 0.9081          |
| 0.0348        | 12.0  | 288  | 0.9272          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
