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# test_clm

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on [Isotonic/human_assistant_conversation](https://huggingface.co/datasets/Isotonic/human_assistant_conversation) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9530
- Perplexity: 7.049969668510691

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": "Isotonic/human_assistant_conversation", "metrics": ["accuracy"], "model-index": [{"name": "Human_assistant_conversation", "results": []}]}
transformers pytorch safetensors gpt2 text-generation generated_from_trainer dataset:Isotonic/human_assistant_conversation license:mit autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #generated_from_trainer #dataset-Isotonic/human_assistant_conversation #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 




# test_clm

This model is a fine-tuned version of gpt2 on Isotonic/human_assistant_conversation dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9530
- Perplexity: 7.049969668510691

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2

# test_clm

This model is a fine-tuned version of gpt2 on Isotonic/human_assistant_conversation dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9530
- Perplexity: 7.049969668510691 ## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #generated_from_trainer #dataset-Isotonic/human_assistant_conversation #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # test_clm

This model is a fine-tuned version of gpt2 on Isotonic/human_assistant_conversation dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9530
- Perplexity: 7.049969668510691 ## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #generated_from_trainer #dataset-Isotonic/human_assistant_conversation #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
# test_clm

This model is a fine-tuned version of gpt2 on Isotonic/human_assistant_conversation dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9530
- Perplexity: 7.049969668510691## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2