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# gpt-expt-sp-v3-K-600-MA-Mac-actions-kmeans-v2

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0160

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.1758        | 25.38  | 5000  | 0.0788          |
| 0.053         | 50.76  | 10000 | 0.0612          |
| 0.0357        | 76.14  | 15000 | 0.0502          |
| 0.0495        | 101.52 | 20000 | 0.0450          |
| 0.0276        | 126.9  | 25000 | 0.0432          |
| 0.0249        | 152.28 | 30000 | 0.0416          |
| 0.0236        | 177.66 | 35000 | 0.0257          |
| 0.0202        | 203.05 | 40000 | 0.0196          |
| 0.0185        | 228.43 | 45000 | 0.0174          |
| 0.0178        | 253.8  | 50000 | 0.0168          |
| 0.0173        | 279.19 | 55000 | 0.0165          |
| 0.0169        | 304.57 | 60000 | 0.0163          |
| 0.0166        | 329.95 | 65000 | 0.0162          |
| 0.0165        | 355.33 | 70000 | 0.0161          |
| 0.0163        | 380.71 | 75000 | 0.0161          |
| 0.0162        | 406.09 | 80000 | 0.0160          |
| 0.0161        | 431.47 | 85000 | 0.0160          |
| 0.0161        | 456.85 | 90000 | 0.0159          |
| 0.016         | 482.23 | 95000 | 0.0160          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt-expt-sp-v3-K-600-MA-Mac-actions-kmeans-v2", "results": []}]}
transformers pytorch gpt2 text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt-expt-sp-v3-K-600-MA-Mac-actions-kmeans-v2
=============================================


This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0160


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: 0.0005
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 500
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 500
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 500
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 500
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1.post200
* Datasets 2.9.0
* Tokenizers 0.13.2