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---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 1_microsoft_deberta_V1.1
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_V1.1
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: 0.7138
- Map@3: 0.8492
- Accuracy: 0.775
## 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: 16
- total_train_batch_size: 32
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Map@3 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 1.6141 | 0.03 | 50 | 1.6087 | 0.6242 | 0.51 |
| 1.336 | 0.05 | 100 | 1.1398 | 0.7550 | 0.645 |
| 0.9441 | 0.08 | 150 | 0.8809 | 0.8150 | 0.7 |
| 0.9279 | 0.11 | 200 | 0.7528 | 0.8383 | 0.73 |
| 0.8639 | 0.13 | 250 | 0.7259 | 0.8525 | 0.76 |
| 0.8255 | 0.16 | 300 | 0.7363 | 0.8592 | 0.785 |
| 0.8411 | 0.19 | 350 | 0.7052 | 0.8483 | 0.76 |
| 0.856 | 0.21 | 400 | 0.7097 | 0.8408 | 0.745 |
| 0.7753 | 0.24 | 450 | 0.6860 | 0.8575 | 0.775 |
| 0.7941 | 0.27 | 500 | 0.7146 | 0.8525 | 0.765 |
| 0.8062 | 0.29 | 550 | 0.7138 | 0.8492 | 0.775 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.9.0
- Tokenizers 0.13.3
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