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# RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-combine-filtered

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3511
- Precision: 0.6276
- Recall: 0.5234
- F1: 0.5708
- Accuracy: 0.8858

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 11   | 0.7773          | 0.0       | 0.0    | 0.0    | 0.7228   |
| No log        | 2.0   | 22   | 0.4915          | 0.4570    | 0.3617 | 0.4038 | 0.8293   |
| No log        | 3.0   | 33   | 0.4246          | 0.4091    | 0.3447 | 0.3741 | 0.8404   |
| No log        | 4.0   | 44   | 0.3725          | 0.4899    | 0.4128 | 0.4480 | 0.8659   |
| No log        | 5.0   | 55   | 0.3628          | 0.6212    | 0.5234 | 0.5681 | 0.8792   |
| No log        | 6.0   | 66   | 0.3492          | 0.6458    | 0.5277 | 0.5808 | 0.8825   |
| No log        | 7.0   | 77   | 0.3453          | 0.6337    | 0.5447 | 0.5858 | 0.8875   |
| No log        | 8.0   | 88   | 0.3546          | 0.6283    | 0.5106 | 0.5634 | 0.8841   |
| No log        | 9.0   | 99   | 0.3491          | 0.6089    | 0.5234 | 0.5629 | 0.8858   |
| No log        | 10.0  | 110  | 0.3511          | 0.6276    | 0.5234 | 0.5708 | 0.8858   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-combine-filtered", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-combine-filtered
=========================================================


This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3511
* Precision: 0.6276
* Recall: 0.5234
* F1: 0.5708
* Accuracy: 0.8858


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3