---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
model-index:
- name: checkpoints_3_14
  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. -->

# checkpoints_3_14

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: 0.9950
- Map@3: 0.7360

## 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: 1
- eval_batch_size: 1
- seed: 0
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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  |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.6075        | 0.04  | 200  | 1.6074          | 0.6027 |
| 1.5444        | 0.08  | 400  | 1.3248          | 0.6428 |
| 1.4506        | 0.13  | 600  | 1.2670          | 0.6707 |
| 1.3635        | 0.17  | 800  | 1.1671          | 0.6850 |
| 1.3478        | 0.21  | 1000 | 1.0909          | 0.7003 |
| 1.3021        | 0.25  | 1200 | 1.0701          | 0.6923 |
| 1.3284        | 0.29  | 1400 | 1.0627          | 0.7085 |
| 1.2869        | 0.34  | 1600 | 1.0645          | 0.7003 |
| 1.2735        | 0.38  | 1800 | 1.1617          | 0.7043 |
| 1.3019        | 0.42  | 2000 | 1.0272          | 0.7120 |
| 1.2824        | 0.46  | 2200 | 1.0781          | 0.7123 |
| 1.2882        | 0.51  | 2400 | 1.0454          | 0.7178 |
| 1.2699        | 0.55  | 2600 | 1.0439          | 0.7225 |
| 1.2165        | 0.59  | 2800 | 1.0208          | 0.7260 |
| 1.2419        | 0.63  | 3000 | 1.0166          | 0.7292 |
| 1.2395        | 0.67  | 3200 | 1.0065          | 0.7310 |
| 1.2368        | 0.72  | 3400 | 1.0429          | 0.7275 |
| 1.2232        | 0.76  | 3600 | 1.0105          | 0.7353 |
| 1.1969        | 0.8   | 3800 | 1.0017          | 0.7370 |
| 1.2451        | 0.84  | 4000 | 0.9982          | 0.7383 |
| 1.2088        | 0.88  | 4200 | 0.9977          | 0.7372 |
| 1.2229        | 0.93  | 4400 | 0.9953          | 0.7367 |
| 1.2612        | 0.97  | 4600 | 0.9950          | 0.7360 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3