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# flan-t5-large-extraction-all-dm_8000-ep10-nonstop

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: 1.5334
- Hint Hit Num: 2.2682
- Hint Precision: 0.4261
- Num: 5.2682
- Gen Len: 18.776

## 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: 12
- eval_batch_size: 96
- 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 Num | Hint Precision | Num    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.1988        | 0.3   | 200  | 1.5870          | 2.6768       | 0.4798         | 5.6224 | 18.9782 |
| 1.976         | 0.6   | 400  | 1.5613          | 2.5624       | 0.4663         | 5.495  | 18.9114 |
| 1.9367        | 0.9   | 600  | 1.5303          | 2.4822       | 0.4551         | 5.4574 | 18.9418 |
| 1.8626        | 1.2   | 800  | 1.5336          | 2.3896       | 0.4403         | 5.3966 | 18.9096 |
| 1.8278        | 1.5   | 1000 | 1.5110          | 2.5016       | 0.4514         | 5.5236 | 18.9486 |
| 1.8115        | 1.8   | 1200 | 1.5116          | 2.2886       | 0.4269         | 5.3196 | 18.9194 |
| 1.776         | 2.1   | 1400 | 1.5212          | 2.3278       | 0.4326         | 5.3394 | 18.8936 |
| 1.7332        | 2.4   | 1600 | 1.5172          | 2.2982       | 0.4323         | 5.2878 | 18.828  |
| 1.7543        | 2.7   | 1800 | 1.5003          | 2.473        | 0.4522         | 5.4414 | 18.9048 |
| 1.7212        | 3.0   | 2000 | 1.5051          | 2.3878       | 0.4389         | 5.4032 | 18.854  |
| 1.6915        | 3.3   | 2200 | 1.5083          | 2.3352       | 0.4347         | 5.3186 | 18.836  |
| 1.6808        | 3.6   | 2400 | 1.5065          | 2.3414       | 0.4367         | 5.321  | 18.8136 |
| 1.6812        | 3.9   | 2600 | 1.5047          | 2.3422       | 0.4376         | 5.3144 | 18.812  |
| 1.6408        | 4.2   | 2800 | 1.5158          | 2.3108       | 0.4297         | 5.33   | 18.8116 |
| 1.6266        | 4.5   | 3000 | 1.5086          | 2.2752       | 0.4227         | 5.329  | 18.8472 |
| 1.6144        | 4.8   | 3200 | 1.5120          | 2.2434       | 0.4192         | 5.283  | 18.8684 |
| 1.6164        | 5.1   | 3400 | 1.5135          | 2.3636       | 0.4356         | 5.3754 | 18.8526 |
| 1.5981        | 5.4   | 3600 | 1.5202          | 2.245        | 0.4201         | 5.2762 | 18.8574 |
| 1.5923        | 5.7   | 3800 | 1.5190          | 2.2462       | 0.4208         | 5.28   | 18.8358 |
| 1.5835        | 6.0   | 4000 | 1.5182          | 2.2812       | 0.4249         | 5.3042 | 18.8182 |
| 1.577         | 6.3   | 4200 | 1.5268          | 2.2928       | 0.4254         | 5.335  | 18.8268 |
| 1.5572        | 6.6   | 4400 | 1.5229          | 2.261        | 0.4237         | 5.276  | 18.7788 |
| 1.5522        | 6.9   | 4600 | 1.5153          | 2.3372       | 0.4323         | 5.3516 | 18.8326 |
| 1.5095        | 7.2   | 4800 | 1.5334          | 2.2108       | 0.4195         | 5.2086 | 18.7338 |
| 1.5568        | 7.5   | 5000 | 1.5243          | 2.302        | 0.4305         | 5.2964 | 18.7742 |
| 1.5373        | 7.8   | 5200 | 1.5277          | 2.2502       | 0.4204         | 5.2868 | 18.8176 |
| 1.5191        | 8.1   | 5400 | 1.5321          | 2.2716       | 0.4247         | 5.2856 | 18.7934 |
| 1.5261        | 8.4   | 5600 | 1.5300          | 2.2938       | 0.4273         | 5.3064 | 18.7828 |
| 1.5202        | 8.7   | 5800 | 1.5337          | 2.2744       | 0.4236         | 5.3086 | 18.8092 |
| 1.4942        | 9.0   | 6000 | 1.5351          | 2.2522       | 0.4239         | 5.257  | 18.7704 |
| 1.4816        | 9.3   | 6200 | 1.5349          | 2.2528       | 0.4247         | 5.2518 | 18.7682 |
| 1.5169        | 9.6   | 6400 | 1.5339          | 2.2698       | 0.4265         | 5.2646 | 18.7736 |
| 1.5007        | 9.9   | 6600 | 1.5334          | 2.269        | 0.4263         | 5.2664 | 18.776  |


### 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-all-dm_8000-ep10-nonstop", "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-all-dm\_8000-ep10-nonstop
==================================================


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: 1.5334
* Hint Hit Num: 2.2682
* Hint Precision: 0.4261
* Num: 5.2682
* Gen Len: 18.776


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: 12
* eval\_batch\_size: 96
* 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: 12
* eval\_batch\_size: 96
* 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: 12
* eval\_batch\_size: 96
* 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: 12
* eval\_batch\_size: 96
* 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