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# unifiedqa-v2-t5-base-1363200-finetuned-qa-doqa

This model is a fine-tuned version of [allenai/unifiedqa-v2-t5-base-1363200](https://huggingface.co/allenai/unifiedqa-v2-t5-base-1363200) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3126

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7767        | 0.05  | 115  | 0.4286          |
| 0.5099        | 0.1   | 230  | 0.3798          |
| 0.4811        | 0.15  | 345  | 0.3663          |
| 0.3736        | 0.2   | 460  | 0.3412          |
| 0.3717        | 0.25  | 575  | 0.3333          |
| 0.3849        | 0.3   | 690  | 0.3532          |
| 0.4335        | 0.35  | 805  | 0.3266          |
| 0.3628        | 0.4   | 920  | 0.3149          |
| 0.3419        | 0.45  | 1035 | 0.3244          |
| 0.3268        | 0.5   | 1150 | 0.3359          |
| 0.3534        | 0.55  | 1265 | 0.3280          |
| 0.3806        | 0.6   | 1380 | 0.3274          |
| 0.3566        | 0.65  | 1495 | 0.3279          |
| 0.4598        | 0.7   | 1610 | 0.3082          |
| 0.3416        | 0.75  | 1725 | 0.3210          |
| 0.3154        | 0.8   | 1840 | 0.3064          |
| 0.3165        | 0.85  | 1955 | 0.3045          |
| 0.2985        | 0.9   | 2070 | 0.3126          |
| 0.327         | 0.95  | 2185 | 0.3090          |
| 0.3246        | 1.0   | 2300 | 0.3122          |
| 0.2495        | 1.05  | 2415 | 0.3105          |
| 0.2271        | 1.1   | 2530 | 0.3143          |
| 0.2611        | 1.15  | 2645 | 0.3149          |
| 0.2819        | 1.2   | 2760 | 0.3140          |
| 0.2583        | 1.25  | 2875 | 0.3072          |
| 0.2708        | 1.3   | 2990 | 0.3112          |
| 0.264         | 1.35  | 3105 | 0.3153          |
| 0.2533        | 1.4   | 3220 | 0.3103          |
| 0.2192        | 1.45  | 3335 | 0.3160          |
| 0.2568        | 1.5   | 3450 | 0.3170          |
| 0.2692        | 1.55  | 3565 | 0.3148          |
| 0.2501        | 1.6   | 3680 | 0.3112          |
| 0.2205        | 1.65  | 3795 | 0.3200          |
| 0.2896        | 1.7   | 3910 | 0.3196          |
| 0.2546        | 1.75  | 4025 | 0.3160          |
| 0.2857        | 1.8   | 4140 | 0.3122          |
| 0.2813        | 1.85  | 4255 | 0.3133          |
| 0.2395        | 1.9   | 4370 | 0.3118          |
| 0.2523        | 1.95  | 4485 | 0.3126          |
| 0.25          | 2.0   | 4600 | 0.3126          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "unifiedqa-v2-t5-base-1363200-finetuned-qa-doqa", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

unifiedqa-v2-t5-base-1363200-finetuned-qa-doqa
==============================================


This model is a fine-tuned version of allenai/unifiedqa-v2-t5-base-1363200 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3126


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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2