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# t5_large_race_cosmos_qa

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the race dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4382
- Accuracy: 0.8023

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.3513        | 1.0   | 10983 | 0.7714   | 0.3165          |
| 0.2109        | 2.0   | 21966 | 0.7986   | 0.3329          |
| 0.0929        | 3.0   | 32949 | 0.4382   | 0.8023          |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0
- Datasets 1.14.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["race"], "metrics": ["accuracy"], "model-index": [{"name": "t5_large_race_cosmos_qa", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:race license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-race #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5\_large\_race\_cosmos\_qa
===========================


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


* Loss: 0.4382
* Accuracy: 0.8023


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: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0
* Datasets 1.14.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0
* Datasets 1.14.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-race #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0
* Datasets 1.14.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-race #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0
* Datasets 1.14.0
* Tokenizers 0.10.3