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# distilrubert_tiny-2nd-finetune-epru

This model is a fine-tuned version of [mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented](https://huggingface.co/mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4467
- Accuracy: 0.8712
- F1: 0.8718
- Precision: 0.8867
- Recall: 0.8712

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4947        | 1.0   | 12   | 0.4142          | 0.8773   | 0.8777 | 0.8907    | 0.8773 |
| 0.2614        | 2.0   | 24   | 0.3178          | 0.9018   | 0.9011 | 0.9069    | 0.9018 |
| 0.2079        | 3.0   | 36   | 0.3234          | 0.8773   | 0.8784 | 0.8850    | 0.8773 |
| 0.1545        | 4.0   | 48   | 0.3729          | 0.8834   | 0.8830 | 0.8946    | 0.8834 |
| 0.1028        | 5.0   | 60   | 0.2964          | 0.9018   | 0.9016 | 0.9073    | 0.9018 |
| 0.0986        | 6.0   | 72   | 0.2971          | 0.9141   | 0.9139 | 0.9152    | 0.9141 |
| 0.0561        | 7.0   | 84   | 0.3482          | 0.8957   | 0.8962 | 0.9023    | 0.8957 |
| 0.0336        | 8.0   | 96   | 0.3731          | 0.8957   | 0.8953 | 0.9014    | 0.8957 |
| 0.0364        | 9.0   | 108  | 0.4467          | 0.8712   | 0.8718 | 0.8867    | 0.8712 |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "distilrubert_tiny-2nd-finetune-epru", "results": []}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

distilrubert\_tiny-2nd-finetune-epru
====================================


This model is a fine-tuned version of mmillet/distilrubert-tiny-cased-conversational-v1\_single\_finetuned\_on\_cedr\_augmented on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4467
* Accuracy: 0.8712
* F1: 0.8718
* Precision: 0.8867
* Recall: 0.8712


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: 0.0001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.20.0
* Pytorch 1.11.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1