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# deberta-v3-large-finetuned-ner-10epochs

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: 0.0776
- Precision: 0.9247
- Recall: 0.9531
- F1: 0.9387
- Accuracy: 0.9890

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0415        | 1.0   | 2261  | 0.0479          | 0.8894    | 0.9572 | 0.9220 | 0.9861   |
| 0.039         | 2.0   | 4522  | 0.0415          | 0.9051    | 0.9498 | 0.9269 | 0.9871   |
| 0.0304        | 3.0   | 6783  | 0.0390          | 0.9086    | 0.9579 | 0.9326 | 0.9883   |
| 0.0275        | 4.0   | 9044  | 0.0383          | 0.9146    | 0.9528 | 0.9333 | 0.9887   |
| 0.0224        | 5.0   | 11305 | 0.0421          | 0.9122    | 0.9583 | 0.9346 | 0.9884   |
| 0.0172        | 6.0   | 13566 | 0.0459          | 0.9204    | 0.9568 | 0.9382 | 0.9890   |
| 0.0122        | 7.0   | 15827 | 0.0561          | 0.9273    | 0.9429 | 0.9350 | 0.9885   |
| 0.0096        | 8.0   | 18088 | 0.0616          | 0.9223    | 0.9568 | 0.9393 | 0.9891   |
| 0.0051        | 9.0   | 20349 | 0.0718          | 0.9240    | 0.9568 | 0.9401 | 0.9890   |
| 0.0034        | 10.0  | 22610 | 0.0776          | 0.9247    | 0.9531 | 0.9387 | 0.9890   |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "deberta-v3-large-finetuned-ner-10epochs", "results": []}]}
transformers pytorch deberta-v2 token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

deberta-v3-large-finetuned-ner-10epochs
=======================================


This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0776
* Precision: 0.9247
* Recall: 0.9531
* F1: 0.9387
* Accuracy: 0.9890


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: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #deberta-v2 #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3