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# mlner-mlwptok-muril

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on the mlner2021 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8331
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8113

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 1.447         | 1.0   | 1389  | 0.9396          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.898         | 2.0   | 2778  | 0.8883          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.859         | 3.0   | 4167  | 0.8721          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8302        | 4.0   | 5556  | 0.8666          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8165        | 5.0   | 6945  | 0.8403          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8143        | 6.0   | 8334  | 0.8376          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8034        | 7.0   | 9723  | 0.8393          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.7766        | 8.0   | 11112 | 0.8383          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.794         | 9.0   | 12501 | 0.8346          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.7858        | 10.0  | 13890 | 0.8331          | 0.0       | 0.0    | 0.0 | 0.8113   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mlner2021"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "mlner-mlwptok-muril", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "mlner2021", "type": "mlner2021", "args": "MLNER2021"}, "metrics": [{"type": "precision", "value": 0.0, "name": "Precision"}, {"type": "recall", "value": 0.0, "name": "Recall"}, {"type": "f1", "value": 0.0, "name": "F1"}, {"type": "accuracy", "value": 0.8112759262826688, "name": "Accuracy"}]}]}]}
transformers pytorch bert token-classification generated_from_trainer dataset:mlner2021 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-mlner2021 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

mlner-mlwptok-muril
===================


This model is a fine-tuned version of google/muril-base-cased on the mlner2021 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8331
* Precision: 0.0
* Recall: 0.0
* F1: 0.0
* Accuracy: 0.8113


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 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### 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 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-mlner2021 #license-apache-2.0 #model-index #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 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-mlner2021 #license-apache-2.0 #model-index #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 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6