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# yt_videos_comments

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0918
- Accuracy: 0.6277

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1201        | 1.53  | 500  | 2.1152          | 0.6220   |
| 2.016         | 3.07  | 1000 | 2.0957          | 0.6254   |
| 1.9383        | 4.6   | 1500 | 2.0898          | 0.6271   |
| 1.8823        | 6.14  | 2000 | 2.0918          | 0.6277   |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0-rc1
- Datasets 2.11.0
- Tokenizers 0.13.3
{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "yt_videos_comments", "results": []}]}
transformers pytorch tensorboard safetensors gpt2 text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

yt\_videos\_comments
====================


This model is a fine-tuned version of gpt2-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0918
* Accuracy: 0.6277


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: 8
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* total\_eval\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000


### Training results



### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0-rc1
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* total\_eval\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000 ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0-rc1
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* total\_eval\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000 ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0-rc1
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 128
* total\_eval\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000### Training results### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0-rc1
* Datasets 2.11.0
* Tokenizers 0.13.3