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# gpt-m-large

This model is a fine-tuned version of [augustocsc/gpt-m-large](https://huggingface.co/augustocsc/gpt-m-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0327

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.0343        | 0.03  | 1000  | 0.0343          |
| 0.0337        | 0.06  | 2000  | 0.0342          |
| 0.0338        | 0.09  | 3000  | 0.0338          |
| 0.0349        | 0.13  | 4000  | 0.0337          |
| 0.034         | 0.16  | 5000  | 0.0335          |
| 0.0342        | 0.19  | 6000  | 0.0334          |
| 0.0341        | 0.22  | 7000  | 0.0333          |
| 0.0339        | 0.25  | 8000  | 0.0333          |
| 0.0336        | 0.28  | 9000  | 0.0331          |
| 0.0335        | 0.31  | 10000 | 0.0330          |
| 0.0334        | 0.35  | 11000 | 0.0330          |
| 0.0331        | 0.38  | 12000 | 0.0328          |
| 0.0332        | 0.41  | 13000 | 0.0328          |
| 0.0327        | 0.44  | 14000 | 0.0327          |
| 0.0331        | 0.47  | 15000 | 0.0327          |
| 0.0335        | 0.5   | 16000 | 0.0327          |
| 0.0333        | 0.53  | 17000 | 0.0327          |
| 0.0333        | 0.57  | 18000 | 0.0327          |
| 0.0333        | 0.6   | 19000 | 0.0327          |
| 0.0332        | 0.63  | 20000 | 0.0327          |
| 0.0331        | 0.66  | 21000 | 0.0327          |
| 0.0328        | 0.69  | 22000 | 0.0327          |
| 0.033         | 0.72  | 23000 | 0.0327          |
| 0.0334        | 0.75  | 24000 | 0.0327          |
| 0.0334        | 0.79  | 25000 | 0.0327          |
| 0.0333        | 0.82  | 26000 | 0.0327          |
| 0.0332        | 0.85  | 27000 | 0.0327          |
| 0.033         | 0.88  | 28000 | 0.0327          |
| 0.033         | 0.91  | 29000 | 0.0327          |
| 0.0331        | 0.94  | 30000 | 0.0327          |
| 0.0335        | 0.97  | 31000 | 0.0327          |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt-m-large", "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-m-large
===========


This model is a fine-tuned version of augustocsc/gpt-m-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0327


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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* 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: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* 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: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2