---
license: mit
base_model: bobbyw/deberta-v3-large_v1_no_entities_with_context
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-large_v1_no_entities_with_context
  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. -->

# deberta-v3-large_v1_no_entities_with_context

This model is a fine-tuned version of [bobbyw/deberta-v3-large_v1_no_entities_with_context](https://huggingface.co/bobbyw/deberta-v3-large_v1_no_entities_with_context) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0260
- Accuracy: 0.0045
- F1: 0.0090
- Precision: 0.0045
- Recall: 1.0
- Learning Rate: 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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.0296        | 1.0   | 540  | 0.0260          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0000 |
| 0.0292        | 2.0   | 1080 | 0.0261          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 1e-05  |
| 0.0306        | 3.0   | 1620 | 0.0260          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 5e-06  |
| 0.0297        | 4.0   | 2160 | 0.0260          | 0.0045   | 0.0090 | 0.0045    | 1.0    | 0.0    |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1