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# layer_9,10,11,12,13

This model is a fine-tuned version of [/pfs/lustrep4/scratch/project_462000259/ajunior/models/rallio3b](https://huggingface.co//pfs/lustrep4/scratch/project_462000259/ajunior/models/rallio3b) on the /pfs/lustrep4/scratch/project_462000259/ajunior/data/arxiv dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3984
- Accuracy: 0.5176

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5584        | 0.05  | 500  | 2.5312          | 0.4997   |
| 2.3975        | 0.1   | 1000 | 2.3984          | 0.5176   |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+gitcb6c422
- Datasets 2.11.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["/pfs/lustrep4/scratch/project_462000259/ajunior/data/arxiv"], "metrics": ["accuracy"], "model-index": [{"name": "layer_9,10,11,12,13", "results": []}]}
transformers pytorch gpt_neox text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt_neox #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

layer\_9,10,11,12,13
====================


This model is a fine-tuned version of /pfs/lustrep4/scratch/project\_462000259/ajunior/models/rallio3b on the /pfs/lustrep4/scratch/project\_462000259/ajunior/data/arxiv dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3984
* Accuracy: 0.5176


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: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+gitcb6c422
* Datasets 2.11.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+gitcb6c422
* Datasets 2.11.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #gpt_neox #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+gitcb6c422
* Datasets 2.11.0
* Tokenizers 0.12.1