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# emozilla/flan-t5-xxl-sat-reading

This model is a fine-tuned version of [google/flan-t5-xxl](https://huggingface.co/google/flan-t5-xxl) on the [emozilla/sat-reading](https://huggingface.co/datasets/emozilla/sat-reading) dataset.

## Model description

This model was trained on the Reading section of several SAT Practice Tests.
It scores better than the original pre-trained model while maintaining zero-shot task performance.
For more information, see the blog post [Language Models vs. The SAT Reading Test](https://jeffq.com/blog/language-models-vs-the-sat-reading-test).

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 38   | 0.2243          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1
- Datasets 2.9.0
- Tokenizers 0.13.2
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emozilla/sat-reading"], "model-index": [{"name": "emozilla/flan-t5-xxl-sat-reading", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:emozilla/sat-reading license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-emozilla/sat-reading #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

emozilla/flan-t5-xxl-sat-reading
================================


This model is a fine-tuned version of google/flan-t5-xxl on the emozilla/sat-reading dataset.


Model description
-----------------


This model was trained on the Reading section of several SAT Practice Tests.
It scores better than the original pre-trained model while maintaining zero-shot task performance.
For more information, see the blog post Language Models vs. The SAT Reading Test.


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* total\_train\_batch\_size: 8
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* total\_train\_batch\_size: 8
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-emozilla/sat-reading #license-apache-2.0 #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: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* total\_train\_batch\_size: 8
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-emozilla/sat-reading #license-apache-2.0 #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: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* total\_train\_batch\_size: 8
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.13.2