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# PhilGPT2-base-clean-on-top-continuous

This model is a fine-tuned version of [bowphs/PhilGPT2-base-clean-on-top](https://huggingface.co/bowphs/PhilGPT2-base-clean-on-top) on the bowphs/multilingual_pretraining dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1594
- Accuracy: 0.2520

## 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
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.3148        | 1.11  | 5000 | 5.1752          | 0.2490   |


### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.5.1
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "datasets": ["bowphs/multilingual_pretraining"], "metrics": ["accuracy"], "model-index": [{"name": "PhilGPT2-base-clean-on-top-continuous", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "bowphs/multilingual_pretraining", "type": "bowphs/multilingual_pretraining"}, "metrics": [{"type": "accuracy", "value": 0.25204334365325076, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:bowphs/multilingual_pretraining model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-bowphs/multilingual_pretraining #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

PhilGPT2-base-clean-on-top-continuous
=====================================


This model is a fine-tuned version of bowphs/PhilGPT2-base-clean-on-top on the bowphs/multilingual\_pretraining dataset.
It achieves the following results on the evaluation set:


* Loss: 5.1594
* Accuracy: 0.2520


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
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2.0


### Training results



### Framework versions


* Transformers 4.23.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.5.1
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2.0 ### Training results ### Framework versions


* Transformers 4.23.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.5.1
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-bowphs/multilingual_pretraining #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #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
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2.0 ### Training results ### Framework versions


* Transformers 4.23.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.5.1
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-bowphs/multilingual_pretraining #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #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
* distributed\_type: multi-GPU
* num\_devices: 2
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2.0### Training results### Framework versions


* Transformers 4.23.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.5.1
* Tokenizers 0.11.6