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# T5-base fine-tuned on CUAD for Legal Contract Review (via QA)

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the cuad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2209

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2809        | 1.0   | 2795  | 0.2331          |
| 0.2459        | 2.0   | 5590  | 0.2253          |
| 0.2355        | 3.0   | 8385  | 0.2220          |
| 0.2212        | 4.0   | 11180 | 0.2203          |
| 0.2068        | 5.0   | 13975 | 0.2197          |
| 0.2085        | 6.0   | 16770 | 0.2194          |
| 0.1968        | 7.0   | 19565 | 0.2199          |
| 0.1906        | 8.0   | 22360 | 0.2200          |
| 0.1909        | 9.0   | 25155 | 0.2208          |
| 0.1788        | 10.0  | 27950 | 0.2209          |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3

{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["cuad"], "model-index": [{"name": "T5-base-cuad-512", "results": []}]}
transformers pytorch safetensors t5 text2text-generation generated_from_trainer en dataset:cuad license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #en #dataset-cuad #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

T5-base fine-tuned on CUAD for Legal Contract Review (via QA)
=============================================================


This model is a fine-tuned version of t5-base on the cuad dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2209


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: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #en #dataset-cuad #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #en #dataset-cuad #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3