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# bert-finetuned-inspec-3-epochs

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the inspec dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2728
- F1: 0.2833
- Precision: 0.2659
- Recall: 0.3030

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.3338        | 1.0   | 125  | 0.2837          | 0.1401 | 0.1510    | 0.1306 |
| 0.2575        | 2.0   | 250  | 0.2658          | 0.2183 | 0.2519    | 0.1927 |
| 0.2259        | 3.0   | 375  | 0.2728          | 0.2833 | 0.2659    | 0.3030 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["inspec"], "metrics": ["f1", "precision", "recall"], "model-index": [{"name": "bert-finetuned-inspec-3-epochs", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "inspec", "type": "inspec", "args": "extraction"}, "metrics": [{"type": "f1", "value": 0.28328008519701814, "name": "F1"}, {"type": "precision", "value": 0.26594090202177295, "name": "Precision"}, {"type": "recall", "value": 0.3030379746835443, "name": "Recall"}]}]}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer dataset:inspec license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-inspec #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-finetuned-inspec-3-epochs
==============================


This model is a fine-tuned version of bert-base-uncased on the inspec dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2728
* F1: 0.2833
* Precision: 0.2659
* Recall: 0.3030


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-inspec #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-inspec #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1