
<!-- 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. -->

# flan-t5-large-extraction-cnndm_2000-all-loss-ep20

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7153
- Hint Hit: 1.7928
- Hint Hit Num: 2.5301
- Hint Precision: 0.4552
- Hint Bleu: 4.636
- Num: 5.479
- Gen Len: 18.9931

## 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: 16
- eval_batch_size: 64
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hint Hit | Hint Hit Num | Hint Precision | Hint Bleu | Num    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:--------------:|:---------:|:------:|:-------:|
| 2.1072        | 1.6   | 200  | 1.7498          | 1.7633   | 2.4767       | 0.4481         | 4.446     | 5.3305 | 18.9731 |
| 1.8307        | 3.2   | 400  | 1.7198          | 1.6971   | 2.4135       | 0.4417         | 4.4059    | 5.2794 | 18.9886 |
| 1.7198        | 4.8   | 600  | 1.7166          | 1.7773   | 2.5021       | 0.4525         | 4.551     | 5.4013 | 18.9849 |
| 1.6269        | 6.4   | 800  | 1.7153          | 1.7928   | 2.5301       | 0.4552         | 4.636     | 5.479  | 18.9931 |
| 1.566         | 8.0   | 1000 | 1.7258          | 1.7252   | 2.4552       | 0.4471         | 4.495     | 5.3751 | 18.9874 |
| 1.5007        | 9.6   | 1200 | 1.7465          | 1.6918   | 2.4154       | 0.4414         | 4.4127    | 5.3099 | 18.9844 |
| 1.4532        | 11.2  | 1400 | 1.7489          | 1.6916   | 2.4277       | 0.4415         | 4.4515    | 5.3719 | 18.9879 |
| 1.416         | 12.8  | 1600 | 1.7607          | 1.7475   | 2.4828       | 0.4475         | 4.5424    | 5.4239 | 18.988  |
| 1.3794        | 14.4  | 1800 | 1.7810          | 1.6556   | 2.384        | 0.4342         | 4.3649    | 5.2977 | 18.9847 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "flan-t5-large-extraction-cnndm_2000-all-loss-ep20", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-large-extraction-cnndm\_2000-all-loss-ep20
==================================================


This model is a fine-tuned version of google/flan-t5-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.7153
* Hint Hit: 1.7928
* Hint Hit Num: 2.5301
* Hint Precision: 0.4552
* Hint Bleu: 4.636
* Num: 5.479
* Gen Len: 18.9931


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: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1