---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: opus-em-deberta-3-large-v2
  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. -->

# opus-em-deberta-3-large-v2

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3445
- F1: 0.0

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:------:|:---------------:|
| 1.2929        | 1.0   | 179  | 0.1942 | 13.4522         |
| 0.1541        | 2.0   | 359  | 0.1942 | 8.4684          |
| 0.1257        | 3.0   | 538  | 0.1942 | 7.6370          |
| 0.1684        | 4.0   | 718  | 0.6376 | 0.7054          |
| 0.0911        | 5.0   | 897  | 0.1942 | 5.1195          |
| 0.145         | 6.0   | 1077 | 0.7984 | 0.2694          |
| 0.1191        | 7.0   | 1256 | 0.2027 | 2.9415          |
| 0.1008        | 8.0   | 1436 | 0.9023 | 0.1785          |
| 0.3698        | 5.0   | 1795 | 0.3514 | 0.0             |
| 0.299         | 6.0   | 2154 | 0.3469 | 0.0             |
| 0.3531        | 7.0   | 2513 | 0.3420 | 0.0             |
| 0.3892        | 8.0   | 2872 | 0.3428 | 0.0             |
| 0.3706        | 9.0   | 3231 | 0.3421 | 0.0             |
| 0.3863        | 10.0  | 3590 | 0.3445 | 0.0             |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0