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# clinical_trial_stop_reasons_custom

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1448
- Accuracy Thresh: 0.9570
- F1 Micro: 0.5300
- F1 Macro: 0.1254
- Confusion Matrix: [[5940   15]
 [ 270  150]]

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh | F1 Micro | F1 Macro | Confusion Matrix           |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:--------:|:--------:|:--------------------------:|
| No log        | 1.0   | 106  | 0.2812          | 0.8328          | 0.0      | 0.0      | [[5955    0]
 [ 420    0]] |
| No log        | 2.0   | 212  | 0.2189          | 0.9382          | 0.0      | 0.0      | [[5955    0]
 [ 420    0]] |
| No log        | 3.0   | 318  | 0.1840          | 0.9489          | 0.0      | 0.0      | [[5955    0]
 [ 420    0]] |
| No log        | 4.0   | 424  | 0.1638          | 0.9485          | 0.4940   | 0.0989   | [[5943   12]
 [ 288  132]] |
| 0.239         | 5.0   | 530  | 0.1526          | 0.9533          | 0.5060   | 0.1018   | [[5943   12]
 [ 277  143]] |
| 0.239         | 6.0   | 636  | 0.1467          | 0.9564          | 0.5077   | 0.1020   | [[5938   17]
 [ 275  145]] |
| 0.239         | 7.0   | 742  | 0.1448          | 0.9570          | 0.5300   | 0.1254   | [[5940   15]
 [ 270  150]] |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu102
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "clinical_trial_stop_reasons_custom", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

clinical\_trial\_stop\_reasons\_custom
======================================


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


* Loss: 0.1448
* Accuracy Thresh: 0.9570
* F1 Micro: 0.5300
* F1 Macro: 0.1254
* Confusion Matrix: [[5940 15]
[ 270 150]]


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.12.1+cu102
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.12.1+cu102
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.12.1+cu102
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.12.1+cu102
* Datasets 2.9.0
* Tokenizers 0.13.2