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# mt5-small-finetuned-amazon-zh-full

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2111
- Rouge1: 10.2419
- Rouge2: 4.7619
- Rougel: 10.2419
- Rougelsum: 10.2419

## 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: 5.6e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 11.4787       | 1.0   | 229  | 4.4488          | 3.1349  | 1.3605 | 3.1349  | 3.1349    |
| 4.8938        | 2.0   | 458  | 3.7642          | 8.2011  | 2.381  | 8.2011  | 8.2011    |
| 4.0429        | 3.0   | 687  | 3.6643          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.7038        | 4.0   | 916  | 3.5566          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.5159        | 5.0   | 1145 | 3.4467          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.3715        | 6.0   | 1374 | 3.4368          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.2854        | 7.0   | 1603 | 3.3713          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.1206        | 8.0   | 1832 | 3.3467          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.0899        | 9.0   | 2061 | 3.2809          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 3.0251        | 10.0  | 2290 | 3.2420          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 2.9903        | 11.0  | 2519 | 3.2251          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 2.9599        | 12.0  | 2748 | 3.2408          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 2.9247        | 13.0  | 2977 | 3.2150          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 2.9131        | 14.0  | 3206 | 3.2121          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |
| 2.8942        | 15.0  | 3435 | 3.2111          | 10.2419 | 4.7619 | 10.2419 | 10.2419   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "datasets": ["amazon_reviews_multi"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-amazon-zh-full", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "amazon_reviews_multi", "type": "amazon_reviews_multi", "config": "zh", "split": "validation", "args": "zh"}, "metrics": [{"type": "rouge", "value": 10.2419, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer dataset:amazon_reviews_multi license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

mt5-small-finetuned-amazon-zh-full
==================================


This model is a fine-tuned version of google/mt5-small on the amazon\_reviews\_multi dataset.
It achieves the following results on the evaluation set:


* Loss: 3.2111
* Rouge1: 10.2419
* Rouge2: 4.7619
* Rougel: 10.2419
* Rougelsum: 10.2419


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: 5.6e-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: 15


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 15 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 15 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #dataset-amazon_reviews_multi #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 15### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2