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# new_merge_mt5

This model is a fine-tuned version of [thanathorn/mt5-cpe-kmutt-thai-sentence-sum](https://huggingface.co/thanathorn/mt5-cpe-kmutt-thai-sentence-sum) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.3352
- eval_rouge1: 0.0868
- eval_rouge2: 0.015
- eval_rougeL: 0.0873
- eval_rougeLsum: 0.0866
- eval_gen_len: 18.9547
- eval_runtime: 160.0435
- eval_samples_per_second: 6.486
- eval_steps_per_second: 1.625
- epoch: 5.14
- step: 2000

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5000

### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "new_merge_mt5", "results": []}]}
transformers pytorch mt5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# new_merge_mt5

This model is a fine-tuned version of thanathorn/mt5-cpe-kmutt-thai-sentence-sum on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.3352
- eval_rouge1: 0.0868
- eval_rouge2: 0.015
- eval_rougeL: 0.0873
- eval_rougeLsum: 0.0866
- eval_gen_len: 18.9547
- eval_runtime: 160.0435
- eval_samples_per_second: 6.486
- eval_steps_per_second: 1.625
- epoch: 5.14
- step: 2000

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5000

### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

# new_merge_mt5

This model is a fine-tuned version of thanathorn/mt5-cpe-kmutt-thai-sentence-sum on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.3352
- eval_rouge1: 0.0868
- eval_rouge2: 0.015
- eval_rougeL: 0.0873
- eval_rougeLsum: 0.0866
- eval_gen_len: 18.9547
- eval_runtime: 160.0435
- eval_samples_per_second: 6.486
- eval_steps_per_second: 1.625
- epoch: 5.14
- step: 2000 ## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5000 ### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #mt5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # new_merge_mt5

This model is a fine-tuned version of thanathorn/mt5-cpe-kmutt-thai-sentence-sum on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.3352
- eval_rouge1: 0.0868
- eval_rouge2: 0.015
- eval_rougeL: 0.0873
- eval_rougeLsum: 0.0866
- eval_gen_len: 18.9547
- eval_runtime: 160.0435
- eval_samples_per_second: 6.486
- eval_steps_per_second: 1.625
- epoch: 5.14
- step: 2000 ## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5000 ### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #mt5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# new_merge_mt5

This model is a fine-tuned version of thanathorn/mt5-cpe-kmutt-thai-sentence-sum on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.3352
- eval_rouge1: 0.0868
- eval_rouge2: 0.015
- eval_rougeL: 0.0873
- eval_rougeLsum: 0.0866
- eval_gen_len: 18.9547
- eval_runtime: 160.0435
- eval_samples_per_second: 6.486
- eval_steps_per_second: 1.625
- epoch: 5.14
- step: 2000## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5000### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2