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# deberta-v3-base-zalo-v2

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4284
- Map@3: 0.4979

## 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: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Map@3  |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.3874        | 0.02  | 25   | 1.3863          | 0.4771 |
| 1.389         | 0.04  | 50   | 1.3863          | 0.4859 |
| 1.3852        | 0.06  | 75   | 1.3862          | 0.5010 |
| 1.3854        | 0.08  | 100  | 1.3856          | 0.4786 |
| 1.3702        | 0.1   | 125  | 1.3823          | 0.4620 |
| 1.2162        | 0.13  | 150  | 1.4487          | 0.4687 |
| 1.0288        | 0.15  | 175  | 1.5260          | 0.4698 |
| 0.995         | 0.17  | 200  | 1.4856          | 0.4786 |
| 0.9684        | 0.19  | 225  | 1.4587          | 0.4750 |
| 0.903         | 0.21  | 250  | 1.4553          | 0.4609 |
| 0.9165        | 0.23  | 275  | 1.4799          | 0.4703 |
| 0.8545        | 0.25  | 300  | 1.4585          | 0.4667 |
| 0.8821        | 0.27  | 325  | 1.4546          | 0.4818 |
| 0.8776        | 0.29  | 350  | 1.4524          | 0.4781 |
| 0.8646        | 0.31  | 375  | 1.4526          | 0.4896 |
| 0.8419        | 0.34  | 400  | 1.4756          | 0.4786 |
| 0.8393        | 0.36  | 425  | 1.4521          | 0.4812 |
| 0.8436        | 0.38  | 450  | 1.4356          | 0.4906 |
| 0.8309        | 0.4   | 475  | 1.4277          | 0.4844 |
| 0.8337        | 0.42  | 500  | 1.4237          | 0.4880 |
| 0.8529        | 0.44  | 525  | 1.4414          | 0.4771 |
| 0.8309        | 0.46  | 550  | 1.4324          | 0.4781 |
| 0.8403        | 0.48  | 575  | 1.4453          | 0.4781 |
| 0.835         | 0.5   | 600  | 1.4234          | 0.4875 |
| 0.8209        | 0.52  | 625  | 1.4603          | 0.4844 |
| 0.8215        | 0.54  | 650  | 1.4406          | 0.4844 |
| 0.818         | 0.57  | 675  | 1.4356          | 0.4776 |
| 0.7983        | 0.59  | 700  | 1.4418          | 0.4833 |
| 0.8485        | 0.61  | 725  | 1.4425          | 0.4844 |
| 0.8236        | 0.63  | 750  | 1.4360          | 0.4865 |
| 0.8173        | 0.65  | 775  | 1.4429          | 0.4880 |
| 0.7871        | 0.67  | 800  | 1.4435          | 0.4865 |
| 0.8116        | 0.69  | 825  | 1.4426          | 0.4974 |
| 0.8227        | 0.71  | 850  | 1.4356          | 0.4943 |
| 0.812         | 0.73  | 875  | 1.4437          | 0.4906 |
| 0.8035        | 0.75  | 900  | 1.4405          | 0.4896 |
| 0.8003        | 0.78  | 925  | 1.4402          | 0.4943 |
| 0.8094        | 0.8   | 950  | 1.4342          | 0.4906 |
| 0.8312        | 0.82  | 975  | 1.4312          | 0.4984 |
| 0.8377        | 0.84  | 1000 | 1.4280          | 0.4974 |
| 0.8448        | 0.86  | 1025 | 1.4278          | 0.4984 |
| 0.8345        | 0.88  | 1050 | 1.4283          | 0.4995 |
| 0.8026        | 0.9   | 1075 | 1.4279          | 0.4995 |
| 0.8066        | 0.92  | 1100 | 1.4282          | 0.4995 |
| 0.8054        | 0.94  | 1125 | 1.4277          | 0.4995 |
| 0.788         | 0.96  | 1150 | 1.4281          | 0.4990 |
| 0.8276        | 0.98  | 1175 | 1.4284          | 0.4979 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/deberta-v3-base", "model-index": [{"name": "deberta-v3-base-zalo-v2", "results": []}]}
transformers safetensors deberta-v2 multiple-choice generated_from_trainer base_model:microsoft/deberta-v3-base license:mit endpoints_compatible region:us