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# flan-t5-large-extraction-cnndm_4000-all-loss-ep10

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: 1.6874
- Hint Hit: 1.6144
- Hint Hit Num: 2.3333
- Hint Precision: 0.4288
- Hint Bleu: 4.2572
- Num: 5.2091
- Gen Len: 18.9881

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hint Hit | Hint Hit Num | Hint Precision | Hint Bleu | Num    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:--------------:|:---------:|:------:|:-------:|
| 2.1171        | 0.8   | 200  | 1.7302          | 1.6677   | 2.3728       | 0.4329         | 4.2712    | 5.1934 | 18.9828 |
| 1.8966        | 1.6   | 400  | 1.7124          | 1.5287   | 2.2068       | 0.4093         | 4.0102    | 4.9193 | 18.9899 |
| 1.8335        | 2.4   | 600  | 1.7060          | 1.5822   | 2.2847       | 0.4226         | 4.1554    | 5.0948 | 18.974  |
| 1.7665        | 3.2   | 800  | 1.6994          | 1.6266   | 2.3195       | 0.4258         | 4.226     | 5.0913 | 18.9835 |
| 1.724         | 4.0   | 1000 | 1.6981          | 1.5722   | 2.2723       | 0.4202         | 4.1168    | 5.0725 | 18.9803 |
| 1.6789        | 4.8   | 1200 | 1.6966          | 1.5552   | 2.262        | 0.4209         | 4.1217    | 5.0892 | 18.9803 |
| 1.6399        | 5.6   | 1400 | 1.6874          | 1.6144   | 2.3333       | 0.4288         | 4.2572    | 5.2091 | 18.9881 |
| 1.6234        | 6.4   | 1600 | 1.6956          | 1.5738   | 2.2816       | 0.4205         | 4.157     | 5.1132 | 18.9886 |
| 1.6102        | 7.2   | 1800 | 1.7029          | 1.5715   | 2.2778       | 0.4211         | 4.133     | 5.1031 | 18.9832 |
| 1.5758        | 8.0   | 2000 | 1.7063          | 1.6003   | 2.3076       | 0.425          | 4.1864    | 5.1369 | 18.9807 |
| 1.5654        | 8.8   | 2200 | 1.7129          | 1.5709   | 2.272        | 0.4193         | 4.1171    | 5.0762 | 18.9784 |
| 1.5697        | 9.6   | 2400 | 1.7069          | 1.6118   | 2.3218       | 0.4277         | 4.2164    | 5.162  | 18.9807 |


### 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_4000-all-loss-ep10", "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\_4000-all-loss-ep10
==================================================


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: 1.6874
* Hint Hit: 1.6144
* Hint Hit Num: 2.3333
* Hint Precision: 0.4288
* Hint Bleu: 4.2572
* Num: 5.2091
* Gen Len: 18.9881


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: 10


### 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: 10 ### 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: 10 ### 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: 10### Training results### Framework versions


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