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# clm-total

This model is a fine-tuned version of [ckiplab/gpt2-base-chinese](https://huggingface.co/ckiplab/gpt2-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8586

## 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: 8
- eval_batch_size: 8
- 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 4.15.0
- Pytorch 1.10.1+cpu
- Datasets 1.17.0
- Tokenizers 0.10.3

{"language": ["zh"], "license": "gpl-3.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "clm-total", "results": []}]}
transformers pytorch gpt2 text-generation generated_from_trainer zh license:gpl-3.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #zh #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# clm-total

This model is a fine-tuned version of ckiplab/gpt2-base-chinese on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8586

## 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: 8
- eval_batch_size: 8
- 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 4.15.0
- Pytorch 1.10.1+cpu
- Datasets 1.17.0
- Tokenizers 0.10.3

# clm-total

This model is a fine-tuned version of ckiplab/gpt2-base-chinese on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8586 ## 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: 8
- eval_batch_size: 8
- 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 4.15.0
- Pytorch 1.10.1+cpu
- Datasets 1.17.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #zh #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # clm-total

This model is a fine-tuned version of ckiplab/gpt2-base-chinese on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8586 ## 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: 8
- eval_batch_size: 8
- 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 4.15.0
- Pytorch 1.10.1+cpu
- Datasets 1.17.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #zh #license-gpl-3.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# clm-total

This model is a fine-tuned version of ckiplab/gpt2-base-chinese on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8586## 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: 8
- eval_batch_size: 8
- 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 4.15.0
- Pytorch 1.10.1+cpu
- Datasets 1.17.0
- Tokenizers 0.10.3