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# distilbert-base-uncased_allagree3

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0937
- Accuracy: 0.9779
- F1: 0.9780

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6418        | 1.0   | 57   | 0.3340          | 0.8805   | 0.8768 |
| 0.1821        | 2.0   | 114  | 0.1088          | 0.9690   | 0.9691 |
| 0.0795        | 3.0   | 171  | 0.0822          | 0.9823   | 0.9823 |
| 0.0385        | 4.0   | 228  | 0.0939          | 0.9646   | 0.9646 |
| 0.0218        | 5.0   | 285  | 0.1151          | 0.9735   | 0.9737 |
| 0.0149        | 6.0   | 342  | 0.1126          | 0.9690   | 0.9694 |
| 0.006         | 7.0   | 399  | 0.0989          | 0.9779   | 0.9780 |
| 0.0093        | 8.0   | 456  | 0.1009          | 0.9779   | 0.9780 |
| 0.0063        | 9.0   | 513  | 0.0899          | 0.9779   | 0.9780 |
| 0.0039        | 10.0  | 570  | 0.0937          | 0.9779   | 0.9780 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["financial_phrasebank"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased_allagree3", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "financial_phrasebank", "type": "financial_phrasebank", "args": "sentences_allagree"}, "metrics": [{"type": "accuracy", "value": 0.9778761061946902, "name": "Accuracy"}, {"type": "f1", "value": 0.9780006392634297, "name": "F1"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:financial_phrasebank license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-financial_phrasebank #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-uncased\_allagree3
==================================


This model is a fine-tuned version of distilbert-base-uncased on the financial\_phrasebank dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0937
* Accuracy: 0.9779
* F1: 0.9780


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: 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: 10


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 10 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-financial_phrasebank #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: 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: 10 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-financial_phrasebank #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: 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: 10### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.3.2
* Tokenizers 0.12.1