
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# LaGPT-continuous

This model is a fine-tuned version of [bowphs/LaGPT-base-correct-tokenizer](https://huggingface.co/bowphs/LaGPT-base-correct-tokenizer) on the bowphs/latin_merged dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8090
- Accuracy: 0.2883

## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0

### Training results



### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.5.1
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "datasets": ["bowphs/latin_merged"], "metrics": ["accuracy"], "model-index": [{"name": "LaGPT-continuous", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "bowphs/latin_merged", "type": "bowphs/latin_merged"}, "metrics": [{"type": "accuracy", "value": 0.28826296647691335, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:bowphs/latin_merged model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-bowphs/latin_merged #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# LaGPT-continuous

This model is a fine-tuned version of bowphs/LaGPT-base-correct-tokenizer on the bowphs/latin_merged dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8090
- Accuracy: 0.2883

## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0

### Training results



### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.5.1
- Tokenizers 0.11.6

# LaGPT-continuous

This model is a fine-tuned version of bowphs/LaGPT-base-correct-tokenizer on the bowphs/latin_merged dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8090
- Accuracy: 0.2883 ## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0 ### Training results ### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.5.1
- Tokenizers 0.11.6
TAGS
#transformers #pytorch #gpt2 #text-generation #generated_from_trainer #dataset-bowphs/latin_merged #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # LaGPT-continuous

This model is a fine-tuned version of bowphs/LaGPT-base-correct-tokenizer on the bowphs/latin_merged dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8090
- Accuracy: 0.2883 ## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0 ### Training results ### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.5.1
- Tokenizers 0.11.6