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# 6b-jilp

This model is a fine-tuned version of [PygmalionAI/pygmalion-6b](https://huggingface.co/PygmalionAI/pygmalion-6b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9014
- Accuracy: 0.1213
- Entropy: 1.8265

## 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: 1e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 99
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Entropy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|
| 2.5421        | 1.0   | 2815  | 1.9824          | 0.1183   | 2.0945  |
| 2.426         | 2.0   | 5630  | 1.9443          | 0.1197   | 1.9446  |
| 2.4504        | 3.0   | 8445  | 1.9248          | 0.1204   | 1.9272  |
| 2.4573        | 4.0   | 11260 | 1.9102          | 0.1211   | 1.8612  |
| 2.4421        | 5.0   | 14075 | 1.9014          | 0.1213   | 1.8265  |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.7.1
- Tokenizers 0.13.3

{"license": "creativeml-openrail-m", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "6b-jilp", "results": []}]}
pytorch tensorboard generated_from_trainer license:creativeml-openrail-m region:us
TAGS
#pytorch #tensorboard #generated_from_trainer #license-creativeml-openrail-m #region-us 

6b-jilp
=======


This model is a fine-tuned version of PygmalionAI/pygmalion-6b on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9014
* Accuracy: 0.1213
* Entropy: 1.8265


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: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 99
* distributed\_type: multi-GPU
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 5.0


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1
* Datasets 2.7.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 99
* distributed\_type: multi-GPU
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1
* Datasets 2.7.1
* Tokenizers 0.13.3
TAGS
#pytorch #tensorboard #generated_from_trainer #license-creativeml-openrail-m #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 12
* eval\_batch\_size: 8
* seed: 99
* distributed\_type: multi-GPU
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 5.0 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1
* Datasets 2.7.1
* Tokenizers 0.13.3